Machine Learning Algorithms | Machine Learning Tutorial | Data Science Tutorial | Edureka
18 likes3,281 views
This Edureka Machine Learning Algorithms tutorial will help you understand all the basics of machine learning and different kind of algorithms along with examples. This tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Data Science concepts. Below are the topics covered in this tutorial: 1. What is an Algorithm? 2. What is Machine Learning? 3. How is a problem solved using Machine Learning? 4. Types of Machine Learning 5. Machine Learning Algorithms
1 of 26
Ad
Recommended
Project communication management
Project communication managementyouness jabbar The document outlines a presentation on project communication management. It discusses the importance of communication management, defining it as ensuring timely and appropriate planning, collection, creation, distribution, storage, retrieval, management, control, monitoring, and disposition of project information. It also covers communicating with stakeholders, various communication forms and tools, developing a communication plan, addressing requirements problems, and controlling communications.
Virtual Private Network VPN
Virtual Private Network VPNFarah M. Altufaili A VPN creates a secure connection over a public network like the Internet by tunneling link layer protocols. It allows remote users to access private networks. VPNs provide security by using an encrypted connection with another IP address and separating IP traffic. Key functions include authentication, access control, confidentiality, and ensuring data integrity. Common protocols are PPTP, L2TP, IPsec, and SSL/TLS.
Counters
CountersKetaki_Pattani This document discusses different types of counters used in digital circuits. It defines a counter as a sequential circuit that cycles through a sequence of states in response to clock pulses. Binary counters count in binary and can count from 0 to 2n-1 with n flip-flops. Asynchronous counters have flip-flops that are not triggered simultaneously by a clock, while synchronous counters use a common clock for all flip-flops. Other counter types include ring counters, Johnson counters, and decade counters. The document provides examples of binary, asynchronous, and synchronous counters and discusses their applications in areas like timing sequences and addressing memory.
Introduction to Machine Learning
Introduction to Machine LearningRahul Jain A short presentation for beginners on Introduction of Machine Learning, What it is, how it works, what all are the popular Machine Learning techniques and learning models (supervised, unsupervised, semi-supervised, reinforcement learning) and how they works with various Industry use-cases and popular examples.
Python OOPs
Python OOPsBinay Kumar Ray This document provides an introduction to object oriented programming in Python. It discusses key OOP concepts like classes, methods, encapsulation, abstraction, inheritance, polymorphism, and more. Each concept is explained in 1-2 paragraphs with examples provided in Python code snippets. The document is presented as a slideshow that is meant to be shared and provide instruction on OOP in Python.
Python Basics
Python Basicstusharpanda88 This document provides an introduction to the Python programming language. It covers Python's background, syntax, types, operators, control flow, functions, classes, tools, and IDEs. Key points include that Python is a multi-purpose, object-oriented language that is interpreted, strongly and dynamically typed. It focuses on readability and has a huge library of modules. Popular Python IDEs include Emacs, Vim, Komodo, PyCharm, and Eclipse.
Naive Bayes Classifier | Naive Bayes Algorithm | Naive Bayes Classifier With ...
Naive Bayes Classifier | Naive Bayes Algorithm | Naive Bayes Classifier With ...Simplilearn This Naive Bayes Classifier tutorial presentation will introduce you to the basic concepts of Naive Bayes classifier, what is Naive Bayes and Bayes theorem, conditional probability concepts used in Bayes theorem, where is Naive Bayes classifier used, how Naive Bayes algorithm works with solved examples, advantages of Naive Bayes. By the end of this presentation, you will also implement Naive Bayes algorithm for text classification in Python.
The topics covered in this Naive Bayes presentation are as follows:
1. What is Naive Bayes?
2. Naive Bayes and Machine Learning
3. Why do we need Naive Bayes?
4. Understanding Naive Bayes Classifier
5. Advantages of Naive Bayes Classifier
6. Demo - Text Classification using Naive Bayes
- - - - - - - -
Simplilearn’s Machine Learning course will make you an expert in Machine Learning, a form of Artificial Intelligence that automates data analysis to enable computers to learn and adapt through experience to do specific tasks without explicit programming. You will master Machine Learning concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, hands-on modeling to develop algorithms and prepare you for the role of Machine Learning Engineer
Why learn Machine Learning?
Machine Learning is rapidly being deployed in all kinds of industries, creating a huge demand for skilled professionals. The Machine Learning market size is expected to grow from USD 1.03 billion in 2016 to USD 8.81 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period.
You can gain in-depth knowledge of Machine Learning by taking our Machine Learning certification training course. With Simplilearn’s Machine Learning course, you will prepare for a career as a Machine Learning engineer as you master concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms. Those who complete the course will be able to:
1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling.
2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project.
3. Acquire thorough knowledge of the mathematical and heuristic aspects of Machine Learning.
4. Understand the concepts and operation of support vector machines, kernel SVM, Naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more.
- - - - - - - -
Lecture 1.pptx
Lecture 1.pptxafsheenfaiq2 This document provides information about a Scratch programming course, including lesson plans, objectives, and instructions. It summarizes that students should maintain a notebook for the Scratch course with dates, topics, standards and objectives for each lesson. It also describes creating accounts on the Scratch website to work on projects and share them in the classroom. The first chapter covers differentiating between programs and programming, and using blocks like motion to make a sprite move on the screen.
Supervised and Unsupervised Learning In Machine Learning | Machine Learning T...
Supervised and Unsupervised Learning In Machine Learning | Machine Learning T...Simplilearn This document provides an overview of machine learning, including:
- Machine learning allows computers to learn from data without being explicitly programmed, through processes like analyzing data, training models on past data, and making predictions.
- The main types of machine learning are supervised learning, which uses labeled training data to predict outputs, and unsupervised learning, which finds patterns in unlabeled data.
- Common supervised learning tasks include classification (like spam filtering) and regression (like weather prediction). Unsupervised learning includes clustering, like customer segmentation, and association, like market basket analysis.
- Supervised and unsupervised learning are used in many areas like risk assessment, image classification, fraud detection, customer analytics, and more
Machine Learning Course | Edureka
Machine Learning Course | EdurekaEdureka! The document describes a machine learning certification training offered by Edureka. It covers topics like introduction to data science, machine learning applications, types of machine learning including supervised, unsupervised and reinforcement learning. For supervised learning, it discusses algorithms like linear regression, logistic regression, decision trees, random forest and Naive Bayes classifier. It also explains machine learning life cycle and concepts like model fitting, clustering and applications of machine learning.
Machine Learning Tutorial Part - 2 | Machine Learning Tutorial For Beginners ...
Machine Learning Tutorial Part - 2 | Machine Learning Tutorial For Beginners ...Simplilearn This presentation on Machine Learning will help you understand what is clustering, K-Means clustering, flowchart to understand K-Means clustering along with demo showing clustering of cars into brands, what is logistic regression, logistic regression curve, sigmoid function and a demo on how to classify a tumor as malignant or benign based on its features. Machine Learning algorithms can help computers play chess, perform surgeries, and get smarter and more personal. K-Means & logistic regression are two widely used Machine learning algorithms which we are going to discuss in this video. Logistic Regression is used to estimate discrete values (usually binary values like 0/1) from a set of independent variables. It helps to predict the probability of an event by fitting data to a logit function. It is also called logit regression. K-means clustering is an unsupervised learning algorithm. In this case, you don't have labeled data unlike in supervised learning. You have a set of data that you want to group into and you want to put them into clusters, which means objects that are similar in nature and similar in characteristics need to be put together. This is what k-means clustering is all about. Now, let us get started and understand K-Means clustering & logistic regression in detail.
Below topics are explained in this Machine Learning tutorial part -2 :
1. Clustering
- What is clustering?
- K-Means clustering
- Flowchart to understand K-Means clustering
- Demo - Clustering of cars based on brands
2. Logistic regression
- What is logistic regression?
- Logistic regression curve & Sigmoid function
- Demo - Classify a tumor as malignant or benign based on features
About Simplilearn Machine Learning course:
A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning.
We recommend this Machine Learning training course for the following professionals in particular:
1. Developers aspiring to be a data scientist or Machine Learning engineer
2. Information architects who want to gain expertise in Machine Learning algorithms
3. Analytics professionals who want to work in Machine Learning or artificial intelligence
4. Graduates looking to build a career in data science and Machine Learning
Learn more at: https://www.simplilearn.com/
Machine Learning
Machine LearningRahul Kumar This is the presentation of Machine learning.Showing the advantage of machine learning and brief introduction of types of machine learning.
Machine Learning Tutorial Part - 1 | Machine Learning Tutorial For Beginners ...
Machine Learning Tutorial Part - 1 | Machine Learning Tutorial For Beginners ...Simplilearn This presentation on Machine Learning will help you understand why Machine Learning came into picture, what is Machine Learning, types of Machine Learning, Machine Learning algorithms with a detailed explanation on linear regression, decision tree & support vector machine and at the end you will also see a use case implementation where we classify whether a recipe is of a cupcake or muffin using SVM algorithm. Machine learning is a core sub-area of artificial intelligence; it enables computers to get into a mode of self-learning without being explicitly programmed. When exposed to new data, these computer programs are enabled to learn, grow, change, and develop by themselves. So, to put simply, the iterative aspect of machine learning is the ability to adapt to new data independently. Now, let us get started with this Machine Learning presentation and understand what it is and why it matters.
Below topics are explained in this Machine Learning presentation:
1. Why Machine Learning?
2. What is Machine Learning?
3. Types of Machine Learning
4. Machine Learning Algorithms
- Linear Regression
- Decision Trees
- Support Vector Machine
5. Use case: Classify whether a recipe is of a cupcake or a muffin using SVM
About Simplilearn Machine Learning course:
A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars. This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning.
Why learn Machine Learning?
Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning
The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period.
We recommend this Machine Learning training course for the following professionals in particular:
1. Developers aspiring to be a data scientist or Machine Learning engineer
2. Information architects who want to gain expertise in Machine Learning algorithms
3. Analytics professionals who want to work in Machine Learning or artificial intelligence
4. Graduates looking to build a career in data science and Machine Learning
Learn more at: https://www.simplilearn.com/
AI vs Machine Learning vs Deep Learning | Machine Learning Training with Pyth...
AI vs Machine Learning vs Deep Learning | Machine Learning Training with Pyth...Edureka! Machine Learning Training with Python: https://www.edureka.co/python )
This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) on "AI vs Machine Learning vs Deep Learning" talks about the differences and relationship between AL, Machine Learning and Deep Learning. Below are the topics covered in this tutorial:
1. AI vs Machine Learning vs Deep Learning
2. What is Artificial Intelligence?
3. Example of Artificial Intelligence
4. What is Machine Learning?
5. Example of Machine Learning
6. What is Deep Learning?
7. Example of Deep Learning
8. Machine Learning vs Deep Learning
Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm
Machine Learning in 10 Minutes | What is Machine Learning? | Edureka
Machine Learning in 10 Minutes | What is Machine Learning? | EdurekaEdureka! YouTube Link: https://youtu.be/qWHi09C3Dq0
** Machine Learning Training with Python: https://www.edureka.co/machine-learning-certification-training**
This Edureka video on 'Machine Learning in 10 Minutes' will help you understand what exactly is Machine Learning and what are the different types of Machine Learning along with some career opportunities that you can achieve through Machine Learning.
Example
What is AI?
What is Machine Learning
Steps for Machine Learning
Types of Machine Learning
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Applications of Machine Learning
What can you be with Machine Learning?
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Machine learning
Machine learningInfoFarm The document is an agenda for a seminar on machine learning techniques and tools. It will cover an introduction to machine learning, common techniques like classification, clustering and regression. It will also discuss tools for machine learning like Apache Mahout, Weka, Spark MLLib and R. Finally, it will include a hands-on demonstration of machine learning algorithms and discuss benefits of using machine learning.
Machine Learning Tutorial | Machine Learning Basics | Machine Learning Algori...
Machine Learning Tutorial | Machine Learning Basics | Machine Learning Algori...Simplilearn This Machine Learning presentation is ideal for beginners to learn Machine Learning from scratch. By the end of this presentation, you will learn why Machine Learning is so important in our lives, what is Machine Learning, the various types of Machine Learning (Supervised, Unsupervised and Reinforcement learning), how do we choose the right Machine Learning solution, what are the different Machine Learning algorithms and how do they work (with simple examples and use-cases).
This Machine Learning presentation will cover the following topics:
1. Life without Machine Learning
2. Life with Machine Learning
3. What is Machine Learning
4. Machine Learning Process
5. Types of Machine Learning
6. Supervised Vs Unsupervised
7. The right Machine Learning solutions
8. Machine Learning Algorithms
9. Use case - Predicting the price of a house using Linear Regression
What is Machine Learning: Machine Learning is an application of Artificial Intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
- - - - - - - -
About Simplilearn Machine Learning course:
A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning.
- - - - - - -
Why learn Machine Learning?
Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning
The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period.
- - - - - - -
Who should take this Machine Learning Training Course?
We recommend this Machine Learning training course for the following professionals in particular:
1. Developers aspiring to be a data scientist or Machine Learning engineer
2. Information architects who want to gain expertise in Machine Learning algorithms
3. Analytics professionals who want to work in Machine Learning or artificial intelligence
4. Graduates looking to build a career in data science and Machine Learning
- - - - - -
Reinforcement Learning Tutorial | Edureka
Reinforcement Learning Tutorial | EdurekaEdureka! YouTube: https://youtu.be/LzaWrmKL1Z4
** Python Data Science Training: https://www.edureka.co/python **
In this PPT on “Reinforcement Learning Tutorial” you will get an in-depth understanding about how reinforcement learning is used in the real world. I’ll be covering the following topics in this session:
Introduction to Machine Learning
What is Reinforcement Learning?
Reinforcement Learning with an analogy
Reinforcement Learning process
Reinforcement Learning Counter-Strike example
Reinforcement Learning Definitions
Reinforcement Learning Concepts
Markov’s Decision Process
Understanding Q-Learning
Demo
Check out our Python Training Playlist: https://goo.gl/Na1p9G
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Data Science vs Machine Learning – What’s The Difference? | Data Science Cour...
Data Science vs Machine Learning – What’s The Difference? | Data Science Cour...Edureka! **Python Data Science Training: https://www.edureka.co/python **
In this video on Data Science vs Machine Learning, we’ll be discussing the importance of Data Science and Machine Learning and we’ll compare them based on a few key parameters. The following topics are covered in this session:
What Is Data Science?
What Is Machine Learning?
Fields Of Data Science
Use Case
Python Training Playlist: https://goo.gl/Na1p9G
Python Blog Series: https://bit.ly/2RVzcVE
Instagram: https://www.instagram.com/edureka_lea...
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
Lecture 1: What is Machine Learning?
Lecture 1: What is Machine Learning?Marina Santini Opening lecture to the Machine Learning for Language Technology course at Uppsala University, Sweden. Autumn 2015
Data Science Full Course | Edureka
Data Science Full Course | EdurekaEdureka! YouTube Link: https://youtu.be/aGu0fbkHhek
** Data Science Master Program: https://www.edureka.co/masters-program/data-scientist-certification **
This Edureka PPT on "Data Science Full Course" provides an end to end, detailed and comprehensive knowledge on Data Science. This Data Science PPT will start with basics of Statistics and Probability and then moves to Machine Learning and Finally ends the journey with Deep Learning and AI. For Data-sets and Codes discussed in this PPT, drop a comment.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Artificial Intelligence Machine Learning Deep Learning Ppt Powerpoint Present...
Artificial Intelligence Machine Learning Deep Learning Ppt Powerpoint Present...SlideTeam Choose our Artificial Intelligence Machine Learning Deep Learning PPT PowerPoint Presentation Slide Templates to understand this popular branch of computer science. Acquaint your audience with the process of building smart, capable machines that can perform intelligent tasks with the help of this neural network PPT presentation. Exhibit the difference between AI, machine learning, and deep learning through this informative robotics PPT design. Elaborate on the wide range of areas that can benefit from artificial intelligence like supply chain, customer experience, human resources, fraud detection, research, and development by taking the aid of this computer science PPT slideshow. Highlight the booming rate of AI business and its future revenue forecast by downloading this thought-provoking and indulging information technology PowerPoint graphics. Save your time and efforts with these pre-ready and professionally crafted content-specific slides. It will educate your audience about this complex process in an easy yet efficient way. Download this AI functioning PowerPoint deck to create a roadmap for the growth and expansion of your business. https://bit.ly/3x135nD
Machine learning
Machine learningRajib Kumar De Machine learning is a method of data analysis that uses algorithms to iteratively learn from data without being explicitly programmed. It allows computers to find hidden insights in data and become better at tasks via experience. Machine learning has many practical applications and is important due to growing data availability, cheaper and more powerful computation, and affordable storage. It is used in fields like finance, healthcare, marketing and transportation. The main approaches are supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Each has real-world examples like loan prediction, market basket analysis, webpage classification, and marketing campaign optimization.
Presentation on supervised learning
Presentation on supervised learningTonmoy Bhagawati This document discusses computational intelligence and supervised learning techniques for classification. It provides examples of applications in medical diagnosis and credit card approval. The goal of supervised learning is to learn from labeled training data to predict the class of new unlabeled examples. Decision trees and backpropagation neural networks are introduced as common supervised learning algorithms. Evaluation methods like holdout validation, cross-validation and performance metrics beyond accuracy are also summarized.
Deep learning - A Visual Introduction
Deep learning - A Visual IntroductionLukas Masuch It’s long ago, approx. 30 years, since AI was not only a topic for Science-Fiction writers, but also a major research field surrounded with huge hopes and investments. But the over-inflated expectations ended in a subsequent crash and followed by a period of absent funding and interest – the so-called AI winter. However, the last 3 years changed everything – again. Deep learning, a machine learning technique inspired by the human brain, successfully crushed one benchmark after another and tech companies, like Google, Facebook and Microsoft, started to invest billions in AI research. “The pace of progress in artificial general intelligence is incredible fast” (Elon Musk – CEO Tesla & SpaceX) leading to an AI that “would be either the best or the worst thing ever to happen to humanity” (Stephen Hawking – Physicist).
What sparked this new Hype? How is Deep Learning different from previous approaches? Are the advancing AI technologies really a threat for humanity? Let’s look behind the curtain and unravel the reality. This talk will explore why Sundar Pichai (CEO Google) recently announced that “machine learning is a core transformative way by which Google is rethinking everything they are doing” and explain why "Deep Learning is probably one of the most exciting things that is happening in the computer industry” (Jen-Hsun Huang – CEO NVIDIA).
Either a new AI “winter is coming” (Ned Stark – House Stark) or this new wave of innovation might turn out as the “last invention humans ever need to make” (Nick Bostrom – AI Philosoph). Or maybe it’s just another great technology helping humans to achieve more.
Machine Learning
Machine LearningBhupender Sharma The Presentation answers various questions such as what is machine learning, how machine learning works, the difference between artificial intelligence, machine learning, deep learning, types of machine learning, and its applications.
Data Science Training | Data Science Tutorial | Data Science Certification | ...
Data Science Training | Data Science Tutorial | Data Science Certification | ...Edureka! This Edureka Data Science Training will help you understand what is Data Science and you will learn about different Data Science components and concepts. This tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Data Science concepts. Below are the topics covered in this tutorial:
1. What is Data Science?
2. Job Roles in Data Science
3. Components of Data Science
4. Concepts of Statistics
5. Power of Data Visualization
6. Introduction to Machine Learning using R
7. Supervised & Unsupervised Learning
8. Classification, Clustering & Recommenders
9. Text Mining & Time Series
10. Deep Learning
To take a structured training on Data Science, you can check complete details of our Data Science Certification Training course here: https://goo.gl/OCfxP2
Introduction of Data Science
Introduction of Data ScienceJason Geng This document provides an overview of data science including what is big data and data science, applications of data science, and system infrastructure. It then discusses recommendation systems in more detail, describing them as systems that predict user preferences for items. A case study on recommendation systems follows, outlining collaborative filtering and content-based recommendation algorithms, and diving deeper into collaborative filtering approaches of user-based and item-based filtering. Challenges with collaborative filtering are also noted.
Machine Learning Interview Questions and Answers
Machine Learning Interview Questions and AnswersSatyam Jaiswal Practice Best Machine Learning Interview Questions and Answers for the best preparation of the machine learning interview. these questions are very popular and asked various times in machine learning interview.
Introduction to Machine Learning
Introduction to Machine LearningSujith Jayaprakash This document introduces machine learning concepts through a webinar presentation. It begins with introductions and definitions of machine learning from Wikipedia and O'Reilly. It then provides examples of artificial intelligence and machine learning applications. The main machine learning concepts covered include supervised learning, unsupervised learning, and reinforcement learning. Supervised learning is described as learning from labeled examples, while unsupervised learning finds patterns in unlabeled data. Reinforcement learning involves an agent interacting with an environment and receiving rewards or punishments to achieve goals. Examples of reinforcement learning applications include autonomous vehicles and game playing agents. In closing, the presenter thanks college administrators and attendees for their participation.
More Related Content
What's hot (20)
Supervised and Unsupervised Learning In Machine Learning | Machine Learning T...
Supervised and Unsupervised Learning In Machine Learning | Machine Learning T...Simplilearn This document provides an overview of machine learning, including:
- Machine learning allows computers to learn from data without being explicitly programmed, through processes like analyzing data, training models on past data, and making predictions.
- The main types of machine learning are supervised learning, which uses labeled training data to predict outputs, and unsupervised learning, which finds patterns in unlabeled data.
- Common supervised learning tasks include classification (like spam filtering) and regression (like weather prediction). Unsupervised learning includes clustering, like customer segmentation, and association, like market basket analysis.
- Supervised and unsupervised learning are used in many areas like risk assessment, image classification, fraud detection, customer analytics, and more
Machine Learning Course | Edureka
Machine Learning Course | EdurekaEdureka! The document describes a machine learning certification training offered by Edureka. It covers topics like introduction to data science, machine learning applications, types of machine learning including supervised, unsupervised and reinforcement learning. For supervised learning, it discusses algorithms like linear regression, logistic regression, decision trees, random forest and Naive Bayes classifier. It also explains machine learning life cycle and concepts like model fitting, clustering and applications of machine learning.
Machine Learning Tutorial Part - 2 | Machine Learning Tutorial For Beginners ...
Machine Learning Tutorial Part - 2 | Machine Learning Tutorial For Beginners ...Simplilearn This presentation on Machine Learning will help you understand what is clustering, K-Means clustering, flowchart to understand K-Means clustering along with demo showing clustering of cars into brands, what is logistic regression, logistic regression curve, sigmoid function and a demo on how to classify a tumor as malignant or benign based on its features. Machine Learning algorithms can help computers play chess, perform surgeries, and get smarter and more personal. K-Means & logistic regression are two widely used Machine learning algorithms which we are going to discuss in this video. Logistic Regression is used to estimate discrete values (usually binary values like 0/1) from a set of independent variables. It helps to predict the probability of an event by fitting data to a logit function. It is also called logit regression. K-means clustering is an unsupervised learning algorithm. In this case, you don't have labeled data unlike in supervised learning. You have a set of data that you want to group into and you want to put them into clusters, which means objects that are similar in nature and similar in characteristics need to be put together. This is what k-means clustering is all about. Now, let us get started and understand K-Means clustering & logistic regression in detail.
Below topics are explained in this Machine Learning tutorial part -2 :
1. Clustering
- What is clustering?
- K-Means clustering
- Flowchart to understand K-Means clustering
- Demo - Clustering of cars based on brands
2. Logistic regression
- What is logistic regression?
- Logistic regression curve & Sigmoid function
- Demo - Classify a tumor as malignant or benign based on features
About Simplilearn Machine Learning course:
A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning.
We recommend this Machine Learning training course for the following professionals in particular:
1. Developers aspiring to be a data scientist or Machine Learning engineer
2. Information architects who want to gain expertise in Machine Learning algorithms
3. Analytics professionals who want to work in Machine Learning or artificial intelligence
4. Graduates looking to build a career in data science and Machine Learning
Learn more at: https://www.simplilearn.com/
Machine Learning
Machine LearningRahul Kumar This is the presentation of Machine learning.Showing the advantage of machine learning and brief introduction of types of machine learning.
Machine Learning Tutorial Part - 1 | Machine Learning Tutorial For Beginners ...
Machine Learning Tutorial Part - 1 | Machine Learning Tutorial For Beginners ...Simplilearn This presentation on Machine Learning will help you understand why Machine Learning came into picture, what is Machine Learning, types of Machine Learning, Machine Learning algorithms with a detailed explanation on linear regression, decision tree & support vector machine and at the end you will also see a use case implementation where we classify whether a recipe is of a cupcake or muffin using SVM algorithm. Machine learning is a core sub-area of artificial intelligence; it enables computers to get into a mode of self-learning without being explicitly programmed. When exposed to new data, these computer programs are enabled to learn, grow, change, and develop by themselves. So, to put simply, the iterative aspect of machine learning is the ability to adapt to new data independently. Now, let us get started with this Machine Learning presentation and understand what it is and why it matters.
Below topics are explained in this Machine Learning presentation:
1. Why Machine Learning?
2. What is Machine Learning?
3. Types of Machine Learning
4. Machine Learning Algorithms
- Linear Regression
- Decision Trees
- Support Vector Machine
5. Use case: Classify whether a recipe is of a cupcake or a muffin using SVM
About Simplilearn Machine Learning course:
A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars. This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning.
Why learn Machine Learning?
Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning
The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period.
We recommend this Machine Learning training course for the following professionals in particular:
1. Developers aspiring to be a data scientist or Machine Learning engineer
2. Information architects who want to gain expertise in Machine Learning algorithms
3. Analytics professionals who want to work in Machine Learning or artificial intelligence
4. Graduates looking to build a career in data science and Machine Learning
Learn more at: https://www.simplilearn.com/
AI vs Machine Learning vs Deep Learning | Machine Learning Training with Pyth...
AI vs Machine Learning vs Deep Learning | Machine Learning Training with Pyth...Edureka! Machine Learning Training with Python: https://www.edureka.co/python )
This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) on "AI vs Machine Learning vs Deep Learning" talks about the differences and relationship between AL, Machine Learning and Deep Learning. Below are the topics covered in this tutorial:
1. AI vs Machine Learning vs Deep Learning
2. What is Artificial Intelligence?
3. Example of Artificial Intelligence
4. What is Machine Learning?
5. Example of Machine Learning
6. What is Deep Learning?
7. Example of Deep Learning
8. Machine Learning vs Deep Learning
Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm
Machine Learning in 10 Minutes | What is Machine Learning? | Edureka
Machine Learning in 10 Minutes | What is Machine Learning? | EdurekaEdureka! YouTube Link: https://youtu.be/qWHi09C3Dq0
** Machine Learning Training with Python: https://www.edureka.co/machine-learning-certification-training**
This Edureka video on 'Machine Learning in 10 Minutes' will help you understand what exactly is Machine Learning and what are the different types of Machine Learning along with some career opportunities that you can achieve through Machine Learning.
Example
What is AI?
What is Machine Learning
Steps for Machine Learning
Types of Machine Learning
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Applications of Machine Learning
What can you be with Machine Learning?
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Machine learning
Machine learningInfoFarm The document is an agenda for a seminar on machine learning techniques and tools. It will cover an introduction to machine learning, common techniques like classification, clustering and regression. It will also discuss tools for machine learning like Apache Mahout, Weka, Spark MLLib and R. Finally, it will include a hands-on demonstration of machine learning algorithms and discuss benefits of using machine learning.
Machine Learning Tutorial | Machine Learning Basics | Machine Learning Algori...
Machine Learning Tutorial | Machine Learning Basics | Machine Learning Algori...Simplilearn This Machine Learning presentation is ideal for beginners to learn Machine Learning from scratch. By the end of this presentation, you will learn why Machine Learning is so important in our lives, what is Machine Learning, the various types of Machine Learning (Supervised, Unsupervised and Reinforcement learning), how do we choose the right Machine Learning solution, what are the different Machine Learning algorithms and how do they work (with simple examples and use-cases).
This Machine Learning presentation will cover the following topics:
1. Life without Machine Learning
2. Life with Machine Learning
3. What is Machine Learning
4. Machine Learning Process
5. Types of Machine Learning
6. Supervised Vs Unsupervised
7. The right Machine Learning solutions
8. Machine Learning Algorithms
9. Use case - Predicting the price of a house using Linear Regression
What is Machine Learning: Machine Learning is an application of Artificial Intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
- - - - - - - -
About Simplilearn Machine Learning course:
A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning.
- - - - - - -
Why learn Machine Learning?
Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning
The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period.
- - - - - - -
Who should take this Machine Learning Training Course?
We recommend this Machine Learning training course for the following professionals in particular:
1. Developers aspiring to be a data scientist or Machine Learning engineer
2. Information architects who want to gain expertise in Machine Learning algorithms
3. Analytics professionals who want to work in Machine Learning or artificial intelligence
4. Graduates looking to build a career in data science and Machine Learning
- - - - - -
Reinforcement Learning Tutorial | Edureka
Reinforcement Learning Tutorial | EdurekaEdureka! YouTube: https://youtu.be/LzaWrmKL1Z4
** Python Data Science Training: https://www.edureka.co/python **
In this PPT on “Reinforcement Learning Tutorial” you will get an in-depth understanding about how reinforcement learning is used in the real world. I’ll be covering the following topics in this session:
Introduction to Machine Learning
What is Reinforcement Learning?
Reinforcement Learning with an analogy
Reinforcement Learning process
Reinforcement Learning Counter-Strike example
Reinforcement Learning Definitions
Reinforcement Learning Concepts
Markov’s Decision Process
Understanding Q-Learning
Demo
Check out our Python Training Playlist: https://goo.gl/Na1p9G
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Data Science vs Machine Learning – What’s The Difference? | Data Science Cour...
Data Science vs Machine Learning – What’s The Difference? | Data Science Cour...Edureka! **Python Data Science Training: https://www.edureka.co/python **
In this video on Data Science vs Machine Learning, we’ll be discussing the importance of Data Science and Machine Learning and we’ll compare them based on a few key parameters. The following topics are covered in this session:
What Is Data Science?
What Is Machine Learning?
Fields Of Data Science
Use Case
Python Training Playlist: https://goo.gl/Na1p9G
Python Blog Series: https://bit.ly/2RVzcVE
Instagram: https://www.instagram.com/edureka_lea...
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
Lecture 1: What is Machine Learning?
Lecture 1: What is Machine Learning?Marina Santini Opening lecture to the Machine Learning for Language Technology course at Uppsala University, Sweden. Autumn 2015
Data Science Full Course | Edureka
Data Science Full Course | EdurekaEdureka! YouTube Link: https://youtu.be/aGu0fbkHhek
** Data Science Master Program: https://www.edureka.co/masters-program/data-scientist-certification **
This Edureka PPT on "Data Science Full Course" provides an end to end, detailed and comprehensive knowledge on Data Science. This Data Science PPT will start with basics of Statistics and Probability and then moves to Machine Learning and Finally ends the journey with Deep Learning and AI. For Data-sets and Codes discussed in this PPT, drop a comment.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Artificial Intelligence Machine Learning Deep Learning Ppt Powerpoint Present...
Artificial Intelligence Machine Learning Deep Learning Ppt Powerpoint Present...SlideTeam Choose our Artificial Intelligence Machine Learning Deep Learning PPT PowerPoint Presentation Slide Templates to understand this popular branch of computer science. Acquaint your audience with the process of building smart, capable machines that can perform intelligent tasks with the help of this neural network PPT presentation. Exhibit the difference between AI, machine learning, and deep learning through this informative robotics PPT design. Elaborate on the wide range of areas that can benefit from artificial intelligence like supply chain, customer experience, human resources, fraud detection, research, and development by taking the aid of this computer science PPT slideshow. Highlight the booming rate of AI business and its future revenue forecast by downloading this thought-provoking and indulging information technology PowerPoint graphics. Save your time and efforts with these pre-ready and professionally crafted content-specific slides. It will educate your audience about this complex process in an easy yet efficient way. Download this AI functioning PowerPoint deck to create a roadmap for the growth and expansion of your business. https://bit.ly/3x135nD
Machine learning
Machine learningRajib Kumar De Machine learning is a method of data analysis that uses algorithms to iteratively learn from data without being explicitly programmed. It allows computers to find hidden insights in data and become better at tasks via experience. Machine learning has many practical applications and is important due to growing data availability, cheaper and more powerful computation, and affordable storage. It is used in fields like finance, healthcare, marketing and transportation. The main approaches are supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Each has real-world examples like loan prediction, market basket analysis, webpage classification, and marketing campaign optimization.
Presentation on supervised learning
Presentation on supervised learningTonmoy Bhagawati This document discusses computational intelligence and supervised learning techniques for classification. It provides examples of applications in medical diagnosis and credit card approval. The goal of supervised learning is to learn from labeled training data to predict the class of new unlabeled examples. Decision trees and backpropagation neural networks are introduced as common supervised learning algorithms. Evaluation methods like holdout validation, cross-validation and performance metrics beyond accuracy are also summarized.
Deep learning - A Visual Introduction
Deep learning - A Visual IntroductionLukas Masuch It’s long ago, approx. 30 years, since AI was not only a topic for Science-Fiction writers, but also a major research field surrounded with huge hopes and investments. But the over-inflated expectations ended in a subsequent crash and followed by a period of absent funding and interest – the so-called AI winter. However, the last 3 years changed everything – again. Deep learning, a machine learning technique inspired by the human brain, successfully crushed one benchmark after another and tech companies, like Google, Facebook and Microsoft, started to invest billions in AI research. “The pace of progress in artificial general intelligence is incredible fast” (Elon Musk – CEO Tesla & SpaceX) leading to an AI that “would be either the best or the worst thing ever to happen to humanity” (Stephen Hawking – Physicist).
What sparked this new Hype? How is Deep Learning different from previous approaches? Are the advancing AI technologies really a threat for humanity? Let’s look behind the curtain and unravel the reality. This talk will explore why Sundar Pichai (CEO Google) recently announced that “machine learning is a core transformative way by which Google is rethinking everything they are doing” and explain why "Deep Learning is probably one of the most exciting things that is happening in the computer industry” (Jen-Hsun Huang – CEO NVIDIA).
Either a new AI “winter is coming” (Ned Stark – House Stark) or this new wave of innovation might turn out as the “last invention humans ever need to make” (Nick Bostrom – AI Philosoph). Or maybe it’s just another great technology helping humans to achieve more.
Machine Learning
Machine LearningBhupender Sharma The Presentation answers various questions such as what is machine learning, how machine learning works, the difference between artificial intelligence, machine learning, deep learning, types of machine learning, and its applications.
Data Science Training | Data Science Tutorial | Data Science Certification | ...
Data Science Training | Data Science Tutorial | Data Science Certification | ...Edureka! This Edureka Data Science Training will help you understand what is Data Science and you will learn about different Data Science components and concepts. This tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Data Science concepts. Below are the topics covered in this tutorial:
1. What is Data Science?
2. Job Roles in Data Science
3. Components of Data Science
4. Concepts of Statistics
5. Power of Data Visualization
6. Introduction to Machine Learning using R
7. Supervised & Unsupervised Learning
8. Classification, Clustering & Recommenders
9. Text Mining & Time Series
10. Deep Learning
To take a structured training on Data Science, you can check complete details of our Data Science Certification Training course here: https://goo.gl/OCfxP2
Introduction of Data Science
Introduction of Data ScienceJason Geng This document provides an overview of data science including what is big data and data science, applications of data science, and system infrastructure. It then discusses recommendation systems in more detail, describing them as systems that predict user preferences for items. A case study on recommendation systems follows, outlining collaborative filtering and content-based recommendation algorithms, and diving deeper into collaborative filtering approaches of user-based and item-based filtering. Challenges with collaborative filtering are also noted.
Similar to Machine Learning Algorithms | Machine Learning Tutorial | Data Science Tutorial | Edureka (20)
Machine Learning Interview Questions and Answers
Machine Learning Interview Questions and AnswersSatyam Jaiswal Practice Best Machine Learning Interview Questions and Answers for the best preparation of the machine learning interview. these questions are very popular and asked various times in machine learning interview.
Introduction to Machine Learning
Introduction to Machine LearningSujith Jayaprakash This document introduces machine learning concepts through a webinar presentation. It begins with introductions and definitions of machine learning from Wikipedia and O'Reilly. It then provides examples of artificial intelligence and machine learning applications. The main machine learning concepts covered include supervised learning, unsupervised learning, and reinforcement learning. Supervised learning is described as learning from labeled examples, while unsupervised learning finds patterns in unlabeled data. Reinforcement learning involves an agent interacting with an environment and receiving rewards or punishments to achieve goals. Examples of reinforcement learning applications include autonomous vehicles and game playing agents. In closing, the presenter thanks college administrators and attendees for their participation.
An Introduction to Machine Learning
An Introduction to Machine LearningVedaj Padman This was part of my inaugural lecture of Summer Internship on Machine Learning at NMAM Institute of Technology, Nitte on 7th June, 2018. A lot more than what was on this presentation was discussed. We spoke on the ethics of choices we make as developers, socio-cultural impact of AI and ML and the political repercussions of deploying ML and AI.
machinecanthink-160226155704.pdf
machinecanthink-160226155704.pdfPranavPatil822557 This document provides an overview of machine learning. It begins with an introduction and discusses the basics, types (supervised, unsupervised, reinforcement learning), technologies, applications, and vision for the next few years. Key points covered include definitions of machine learning, examples of applications (search engines, spam filters, personalized recommendations), and descriptions of different problem types (classification, regression, clustering) and learning approaches (decision trees, neural networks, Bayesian methods).
Data Science Tutorial | Introduction To Data Science | Data Science Training ...
Data Science Tutorial | Introduction To Data Science | Data Science Training ...Edureka! This Edureka Data Science tutorial will help you understand in and out of Data Science with examples. This tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Data Science concepts. Below are the topics covered in this tutorial:
1. Why Data Science?
2. What is Data Science?
3. Who is a Data Scientist?
4. How a Problem is Solved in Data Science?
5. Data Science Components
Machine Can Think
Machine Can ThinkRahul Jaiman This document provides an overview of machine learning. It begins with an introduction and definitions, explaining that machine learning allows computers to learn without being explicitly programmed by exploring algorithms that can learn from data. The document then discusses the different types of machine learning problems including supervised learning, unsupervised learning, and reinforcement learning. It provides examples and applications of each type. The document also covers popular machine learning techniques like decision trees, artificial neural networks, and frameworks/tools used for machine learning.
Sentiment Analysis | Machine Learning Algorithms | Data Science Tutorial | Ed...
Sentiment Analysis | Machine Learning Algorithms | Data Science Tutorial | Ed...Edureka! This Edureka Sentiment Analysis tutorial will help you understand all the basics of Sentiment Analysis algorithm along with examples. This tutorial also has an interesting demo on Sentiment Analysis in R - El Clasico Sentiment Analysis. Below are the topics covered in this tutorial:
1. What is Machine Learning?
2. Why Sentiment Analysis?
3. What is Sentiment Analysis?
4. How Sentiment Analysis Works?
5. Sentiment Analysis Demo - El Clasico
6. Sentiment Analysis Use Case
Machine Learning by Rj
Machine Learning by RjShree M.L.Kakadiya MCA mahila college, Amreli This document provides an overview of machine learning presented by Mr. Raviraj Solanki. It discusses topics like introduction to machine learning, model preparation, modelling and evaluation. It defines key concepts like algorithms, models, predictor variables, response variables, training data and testing data. It also explains the differences between human learning and machine learning, types of machine learning including supervised learning and unsupervised learning. Supervised learning is further divided into classification and regression problems. Popular algorithms for supervised learning like random forest, decision trees, logistic regression, support vector machines, linear regression, regression trees and more are also mentioned.
introduction to machine learning
introduction to machine learningJohnson Ubah This document provides an introduction to machine learning and data science. It discusses key concepts like supervised vs. unsupervised learning, classification algorithms, overfitting and underfitting data. It also addresses challenges like having bad quality or insufficient training data. Python and MATLAB are introduced as suitable software for machine learning projects.
INTERNSHIP ON MAcHINE LEARNING.pptx
INTERNSHIP ON MAcHINE LEARNING.pptxsrikanthkallem1 The document discusses machine learning methods including supervised learning, unsupervised learning, and reinforcement learning. It provides examples of how each method is used, such as using historical data for prediction in supervised learning and organizing unlabeled data in unsupervised learning. Random forest, an ensemble supervised learning algorithm, is also summarized. It states random forest combines decision trees for improved performance and discusses its use in sectors like banking, medicine, land use, and marketing.
Types of machine learning
Types of machine learningHimaniAloona There are three main types of machine learning: supervised learning, unsupervised learning, and reinforcement learning. Supervised learning uses labeled data to train models to make predictions, unsupervised learning finds patterns in unlabeled data through clustering, and reinforcement learning allows agents to learn behaviors through rewards and punishments from its environment.
Machine Learning - Deep Learning
Machine Learning - Deep LearningOluwasegun Matthew In a world of data explosion, the rate of data generation and consumption is on the increasing side, there comes the buzzword - Big Data.
Big Data is the concept of fast-moving, large-volume data in varying dimensions (sources) and
highly unpredicted sources.
The 4Vs of Big Data
● Volume - Scale of Data
● Velocity - Analysis of Streaming Data
● Variety - Different forms of Data
● Veracity - Uncertainty of Data
With increasing data availability, the new trend in the industry demands not just data collection,
but making ample sense of acquired data - thereby, the concept of Data Analytics.
Taking it a step further to further make a futuristic prediction and realistic inferences - the concept
of Machine Learning.
A blend of both gives a robust analysis of data for the past, now and the future.
There is a thin line between data analytics and Machine learning which becomes very obvious
when you dig deep.
Machine Learning Interview Questions
Machine Learning Interview QuestionsRock Interview Machine Learning jobs are one of the top emerging jobs in the industry currently, and standing out during an interview is key for landing your desired job. Here are some Machine Learning interview questions you should know about, if you plan to build a successful career in the field.
Introduction to Data Science
Introduction to Data ScienceChristy Abraham Joy A brief introduction to DataScience with explaining of the concepts, algorithms, machine learning, supervised and unsupervised learning, clustering, statistics, data preprocessing, real-world applications etc.
It's part of a Data Science Corner Campaign where I will be discussing the fundamentals of DataScience, AIML, Statistics etc.
Supervised learning techniques and applications
Supervised learning techniques and applicationsBenjaminlapid1 Discover the fundamentals of supervised learning in this guide. Learn about its techniques, applications, and best practices for optimal results.
Introduction to machine learning
Introduction to machine learningOluwasegun Matthew In a world of data explosion, the rate of data generation and consumption is on the increasing side,
there comes the buzzword - Big Data.
Big Data is the concept of fast-moving, large-volume data in varying dimensions (sources) and
highly unpredicted sources.
The 4Vs of Big Data
● Volume - Scale of Data
● Velocity - Analysis of Streaming Data
● Variety - Different forms of Data
● Veracity - Uncertainty of Data
With increasing data availability, the new trend in the industry demands not just data collection but making an ample sense of acquired data - thereby, the concept of Data Analytics.
Taking it a step further to further make futuristic prediction and realistic inferences - the concept
of Machine Learning.
A blend of both gives a robust analysis of data for the past, now and the future.
There is a thin line between data analytics and Machine learning which becomes very obvious
when you dig deep.
Ad
More from Edureka! (20)
What to learn during the 21 days Lockdown | Edureka
What to learn during the 21 days Lockdown | EdurekaEdureka! Register Here: https://resources.edureka.co/21-days-learning-plan-webinar/
In light of the complete national lockdown for 21 days, we invite you to join a FREE webinar by renowned Mentor and Advisor, Nitin Gupta as he helps you create a 21-day learning gameplan to maximize returns for your career.
The webinar will help freshers and experienced professionals to capitalize on these 21 days and figure out the best technologies to learn while confined to home.
You will also get all your questions and doubts resolved in real-time.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Meetup: https://www.meetup.com/edureka/
Top 10 Dying Programming Languages in 2020 | Edureka
Top 10 Dying Programming Languages in 2020 | EdurekaEdureka! YouTube Link: https://youtu.be/LSM7hD6GM4M
Get Edureka Certified in Trending Programming Languages: https://www.edureka.co
In this highly competitive IT industry, everyone wants to learn programming languages that will keep them ahead of the game. But knowing what to learn so you gain the most out of your knowledge is a whole other ball game. So, we at Edureka have prepared a list of Top 10 Dying Programming Languages 2020 that will help you to make the right choice for your career. Meanwhile, if you ever wondered about which languages are slated for continuing uptake and possible greatness, we have a list for that, too.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Top 5 Trending Business Intelligence Tools | Edureka
Top 5 Trending Business Intelligence Tools | EdurekaEdureka! YouTube Link: https://youtu.be/eEwq_mPd1iI
Edureka BI Certification Training Courses: https://www.edureka.co/bi-and-visualization-certification-courses
Receiving insights and finding trends is absolutely critical for businesses to scale and adapt as the years go on. This is exactly what business intelligence does and the best thing about these software solutions is that their potential uses are practically unlimited.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Tableau Tutorial for Data Science | Edureka
Tableau Tutorial for Data Science | EdurekaEdureka! YouTube Link:https://youtu.be/ZHNdSKMluI0
Edureka Tableau Certification Training: https://www.edureka.co/tableau-certification-training
This Edureka's PPT on "Tableau for Data Science" will help you to utilize Tableau as a tool for Data Science, not only for engagement but also comprehension efficiency. Through this PPT, you will learn to gain the maximum amount of insight with the least amount of effort.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Python Programming Tutorial | Edureka
Python Programming Tutorial | EdurekaEdureka! YouTube Link:https://youtu.be/CVv8zhYEjUE
Edureka Python Certification Training: https://www.edureka.co/data-science-python-certification-course
This Edureka PPT on 'Python Programming' will help you learn Python programming basics with the help of interesting hands-on implementations.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Top 5 PMP Certifications | Edureka
Top 5 PMP Certifications | EdurekaEdureka! YouTube Link:https://youtu.be/LvgqSMlIXFs
Get Edureka Certified in Trending Project Management Certifications: https://www.edureka.co/project-management-and-methodologies-certification-courses
Whether you want to scale up your career or are trying to switch your career path, Project Management Certifications seems to be a perfect choice in either case. So, we at Edureka have prepared a list of Top 5 Project Management Certifications that you must check out in 2020 for a major career boost.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Top Maven Interview Questions in 2020 | Edureka
Top Maven Interview Questions in 2020 | EdurekaEdureka! YouTube Link: https://youtu.be/5iTcAR4fScM
**DevOps Certification Courses - https://www.edureka.co/devops-certification-training***
This video on 'Maven Interview Questions' discusses the most frequently asked Maven Interview Questions. This PPT will help give you a detailed explanation of the topics which will help you in acing the interviews.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Linux Mint Tutorial | Edureka
Linux Mint Tutorial | EdurekaEdureka! YouTube Link: https://youtu.be/xHUiYEIcY_I
** Linux Administration Certification Training - https://www.edureka.co/linux-admin **
Linux Mint is the first operating system that people from Windows or Mac are drawn towards when they have to switch to Linux in their work environment. Linux Mint has been around since the year 2006 and has grown and matured into a very user-friendly OS. Do watch the PPT till the very end to see all the demonstrations.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
How to Deploy Java Web App in AWS| Edureka
How to Deploy Java Web App in AWS| EdurekaEdureka! YouTube Link:https://youtu.be/Ozc5Yu_IcaI
** Edureka AWS Architect Certification Training - https://www.edureka.co/aws-certification-training**
This Edureka PPT shows how to deploy a java web application in AWS using AWS Elastic Beanstalk. It also describes the advantages of using AWS for this purpose.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Importance of Digital Marketing | Edureka
Importance of Digital Marketing | EdurekaEdureka! YouTube Link:https://youtu.be/phPCkkWT76k
*** Edureka Digital Marketing Course: https://www.edureka.co/post-graduate/digital-marketing-certification***
This Edureka PPT on "Top 10 Reasons to Learn Digital Marketing" will help you understand why you should take up Digital Marketing
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
RPA in 2020 | Edureka
RPA in 2020 | EdurekaEdureka! YouTube Link: https://youtu.be/R132INtDg9k
** RPA Training: https://www.edureka.co/robotic-process-automation-training**
This PPT on RPA in 2020 will provide a glimpse of the accomplishments and benefits provided by RPA. Also, it will list out the new changes and technologies that will collaborate with RPA in 2020.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Email Notifications in Jenkins | Edureka
Email Notifications in Jenkins | EdurekaEdureka! YouTube Link: https://youtu.be/mb8WOHejlT8
**DevOps Certification Courses - https://www.edureka.co/devops-certification-training **
This PPT shows how to configure Jenkins to receive email notifications. It also includes a demo that shows how to do it in 6 simple steps in the Windows machine.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
EA Algorithm in Machine Learning | Edureka
EA Algorithm in Machine Learning | EdurekaEdureka! YouTube Link: https://youtu.be/DIADjJXrgps
** Machine Learning Certification Training: https://www.edureka.co/machine-learning-certification-training **
This Edureka PPT on 'EM Algorithm In Machine Learning' covers the EM algorithm along with the problem of latent variables in maximum likelihood and Gaussian mixture model.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Cognitive AI Tutorial | Edureka
Cognitive AI Tutorial | EdurekaEdureka! Cognitive computing aims to mimic human reasoning and behavior to solve complex problems. It works by simulating human thought processes through adaptive, interactive, iterative and contextual means. Cognitive computing supplements human decision making in sectors like customer service and healthcare, while artificial intelligence focuses more on autonomous decision making with applications in finance, security and more. A use case of cognitive AI is using it to assess skills, find relevant jobs, negotiate pay, suggest career paths and provide salary comparisons and job openings to help humans.
AWS Cloud Practitioner Tutorial | Edureka
AWS Cloud Practitioner Tutorial | EdurekaEdureka! YouTube Link: https://youtu.be/0djPrlaxx_U
Edureka AWS Architect Certification Training - https://www.edureka.co/aws-certification-training
This Edureka PPT on AWS Cloud Practitioner will provide a complete guide to your AWS Cloud Practitioner Certification exam. It will explain the exam details, objectives, why you should get certified and also how AWS certification will help your career.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Blue Prism Top Interview Questions | Edureka
Blue Prism Top Interview Questions | EdurekaEdureka! YouTube Link: https://youtu.be/ykbRdUNIbyQ
** RPA Training: https://www.edureka.co/robotic-process-automation-certification-courses**
This PPT on Blue Prism Interview Questions will cover the Top 50 Blue Prism related questions asked in your interviews.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Big Data on AWS Tutorial | Edureka 
Big Data on AWS Tutorial | Edureka Edureka! YouTube Link: https://youtu.be/ge4qhkl9uKg
AWS Architect Certification Training: https://www.edureka.co/aws-certification-training
This PPT will help you in understanding how AWS deals smartly with Big Data. It also shows how AWS can solve Big Data challenges with ease.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
A star algorithm | A* Algorithm in Artificial Intelligence | Edureka
A star algorithm | A* Algorithm in Artificial Intelligence | EdurekaEdureka! YouTube Link: https://youtu.be/amlkE0g-YFU
** Artificial Intelligence and Deep Learning: https://www.edureka.co/ai-deep-learni... **
This Edureka PPT on 'A Star Algorithm' teaches you all about the A star Algorithm, the uses, advantages and disadvantages and much more. It also shows you how the algorithm can be implemented practically and has a comparison between the Dijkstra and itself.
Check out our playlist for more videos: http://bit.ly/2taym8X
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Kubernetes Installation on Ubuntu | Edureka
Kubernetes Installation on Ubuntu | EdurekaEdureka! YouTube Link: https://youtu.be/UWg3ORRRF60
Kubernetes Certification: https://www.edureka.co/kubernetes-certification
This Edureka PPT will help you set up a Kubernetes cluster having 1 master and 1 node. The detailed step by step instructions is demonstrated in this PPT.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Introduction to DevOps | Edureka
Introduction to DevOps | EdurekaEdureka! YouTube Link: https://youtu.be/GJQ36pIYbic
DevOps Training: https://www.edureka.co/devops-certification-training
This Edureka DevOps Tutorial for Beginners talks about What is DevOps and how it works. You will learn about several DevOps tools (Git, Jenkins, Docker, Puppet, Ansible, Nagios) involved at different DevOps stages such as version control, continuous integration, continuous delivery, continuous deployment, continuous monitoring.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Ad
Recently uploaded (20)
Secure Access with Azure Active Directory
Secure Access with Azure Active DirectoryVICTOR MAESTRE RAMIREZ Secure Access with Azure Active Directory
Oracle Cloud Infrastructure AI Foundations
Oracle Cloud Infrastructure AI FoundationsVICTOR MAESTRE RAMIREZ Oracle Cloud Infrastructure AI Foundations
National Fuels Treatments Initiative: Building a Seamless Map of Hazardous Fu...
National Fuels Treatments Initiative: Building a Seamless Map of Hazardous Fu...Safe Software The National Fuels Treatments Initiative (NFT) is transforming wildfire mitigation by creating a standardized map of nationwide fuels treatment locations across all land ownerships in the United States. While existing state and federal systems capture this data in diverse formats, NFT bridges these gaps, delivering the first truly integrated national view. This dataset will be used to measure the implementation of the National Cohesive Wildland Strategy and demonstrate the positive impact of collective investments in hazardous fuels reduction nationwide. In Phase 1, we developed an ETL pipeline template in FME Form, leveraging a schema-agnostic workflow with dynamic feature handling intended for fast roll-out and light maintenance. This was key as the initiative scaled from a few to over fifty contributors nationwide. By directly pulling from agency data stores, oftentimes ArcGIS Feature Services, NFT preserves existing structures, minimizing preparation needs. External mapping tables ensure consistent attribute and domain alignment, while robust change detection processes keep data current and actionable. Now in Phase 2, we’re migrating pipelines to FME Flow to take advantage of advanced scheduling, monitoring dashboards, and automated notifications to streamline operations. Join us to explore how this initiative exemplifies the power of technology, blending FME, ArcGIS Online, and AWS to solve a national business problem with a scalable, automated solution.
Agentic AI: Beyond the Buzz- LangGraph Studio V2
Agentic AI: Beyond the Buzz- LangGraph Studio V2Shashikant Jagtap Presentation given at the LangChain community meetup London
https://lu.ma/9d5fntgj
Coveres
Agentic AI: Beyond the Buzz
Introduction to AI Agent and Agentic AI
Agent Use case and stats
Introduction to LangGraph
Build agent with LangGraph Studio V2
June Patch Tuesday
June Patch TuesdayIvanti Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Your startup on AWS - How to architect and maintain a Lean and Mean account J...
Your startup on AWS - How to architect and maintain a Lean and Mean account J...angelo60207 Prevent infrastructure costs from becoming a significant line item on your startup’s budget! Serial entrepreneur and software architect Angelo Mandato will share his experience with AWS Activate (startup credits from AWS) and knowledge on how to architect a lean and mean AWS account ideal for budget minded and bootstrapped startups. In this session you will learn how to manage a production ready AWS account capable of scaling as your startup grows for less than $100/month before credits. We will discuss AWS Budgets, Cost Explorer, architect priorities, and the importance of having flexible, optimized Infrastructure as Code. We will wrap everything up discussing opportunities where to save with AWS services such as S3, EC2, Load Balancers, Lambda Functions, RDS, and many others.
Artificial Intelligence in the Nonprofit Boardroom.pdf
Artificial Intelligence in the Nonprofit Boardroom.pdfOnBoard OnBoard recently partnered with Microsoft Tech for Social Impact on the AI in the Nonprofit Boardroom Survey, an initiative designed to uncover the current and future role of artificial intelligence in nonprofit governance.
Bridging the divide: A conversation on tariffs today in the book industry - T...
Bridging the divide: A conversation on tariffs today in the book industry - T...BookNet Canada A collaboration-focused conversation on the recently imposed US and Canadian tariffs where speakers shared insights into the current legislative landscape, ongoing advocacy efforts, and recommended next steps. This event was presented in partnership with the Book Industry Study Group.
Link to accompanying resource: https://bnctechforum.ca/sessions/bridging-the-divide-a-conversation-on-tariffs-today-in-the-book-industry/
Presented by BookNet Canada and the Book Industry Study Group on May 29, 2025 with support from the Department of Canadian Heritage.
If You Use Databricks, You Definitely Need FME
If You Use Databricks, You Definitely Need FMESafe Software DataBricks makes it easy to use Apache Spark. It provides a platform with the potential to analyze and process huge volumes of data. Sounds awesome. The sales brochure reads as if it is a can-do-all data integration platform. Does it replace our beloved FME platform or does it provide opportunities for FME to shine? Challenge accepted
vertical-cnc-processing-centers-drillteq-v-200-en.pdf
vertical-cnc-processing-centers-drillteq-v-200-en.pdfAmirStern2 מכונות CNC קידוח אנכיות הן הבחירה הנכונה והטובה ביותר לקידוח ארונות וארגזים לייצור רהיטים. החלק נוסע לאורך ציר ה-x באמצעות ציר דיגיטלי מדויק, ותפוס ע"י צבת מכנית, כך שאין צורך לבצע setup (התאמות) לגדלים שונים של חלקים.
Providing an OGC API Processes REST Interface for FME Flow
Providing an OGC API Processes REST Interface for FME FlowSafe Software This presentation will showcase an adapter for FME Flow that provides REST endpoints for FME Workspaces following the OGC API Processes specification. The implementation delivers robust, user-friendly API endpoints, including standardized methods for parameter provision. Additionally, it enhances security and user management by supporting OAuth2 authentication. Join us to discover how these advancements can elevate your enterprise integration workflows and ensure seamless, secure interactions with FME Flow.
TrustArc Webinar - 2025 Global Privacy Survey
TrustArc Webinar - 2025 Global Privacy SurveyTrustArc How does your privacy program compare to your peers? What challenges are privacy teams tackling and prioritizing in 2025?
In the sixth annual Global Privacy Benchmarks Survey, we asked global privacy professionals and business executives to share their perspectives on privacy inside and outside their organizations. The annual report provides a 360-degree view of various industries' priorities, attitudes, and trends. See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar features an expert panel discussion and data-driven insights to help you navigate the shifting privacy landscape. Whether you are a privacy officer, legal professional, compliance specialist, or security expert, this session will provide actionable takeaways to strengthen your privacy strategy.
This webinar will review:
- The emerging trends in data protection, compliance, and risk
- The top challenges for privacy leaders, practitioners, and organizations in 2025
- The impact of evolving regulations and the crossroads with new technology, like AI
Predictions for the future of privacy in 2025 and beyond
Kubernetes Security Act Now Before It’s Too Late
Kubernetes Security Act Now Before It’s Too LateMichael Furman In today's cloud-native landscape, Kubernetes has become the de facto standard for orchestrating containerized applications, but its inherent complexity introduces unique security challenges. Are you one YAML away from disaster?
This presentation, "Kubernetes Security: Act Now Before It’s Too Late," is your essential guide to understanding and mitigating the critical security risks within your Kubernetes environments. This presentation dives deep into the OWASP Kubernetes Top Ten, providing actionable insights to harden your clusters.
We will cover:
The fundamental architecture of Kubernetes and why its security is paramount.
In-depth strategies for protecting your Kubernetes Control Plane, including kube-apiserver and etcd.
Crucial best practices for securing your workloads and nodes, covering topics like privileged containers, root filesystem security, and the essential role of Pod Security Admission.
Don't wait for a breach. Learn how to identify, prevent, and respond to Kubernetes security threats effectively.
It's time to act now before it's too late!
Azure vs AWS Which Cloud Platform Is Best for Your Business in 2025
Azure vs AWS Which Cloud Platform Is Best for Your Business in 2025Infrassist Technologies Pvt. Ltd. Azure vs. AWS is a common comparison when businesses evaluate cloud platforms for performance, flexibility, and cost-efficiency.
Domino IQ – Was Sie erwartet, erste Schritte und Anwendungsfälle
Domino IQ – Was Sie erwartet, erste Schritte und Anwendungsfällepanagenda Webinar Recording: https://www.panagenda.com/webinars/domino-iq-was-sie-erwartet-erste-schritte-und-anwendungsfalle/
HCL Domino iQ Server – Vom Ideenportal zur implementierten Funktion. Entdecken Sie, was es ist, was es nicht ist, und erkunden Sie die Chancen und Herausforderungen, die es bietet.
Wichtige Erkenntnisse
- Was sind Large Language Models (LLMs) und wie stehen sie im Zusammenhang mit Domino iQ
- Wesentliche Voraussetzungen für die Bereitstellung des Domino iQ Servers
- Schritt-für-Schritt-Anleitung zur Einrichtung Ihres Domino iQ Servers
- Teilen und diskutieren Sie Gedanken und Ideen, um das Potenzial von Domino iQ zu maximieren
Establish Visibility and Manage Risk in the Supply Chain with Anchore SBOM
Establish Visibility and Manage Risk in the Supply Chain with Anchore SBOMAnchore Over 70% of any given software application consumes open source software (most likely not even from the original source) and only 15% of organizations feel confident in their risk management practices.
With the newly announced Anchore SBOM feature, teams can start safely consuming OSS while mitigating security and compliance risks. Learn how to import SBOMs in industry-standard formats (SPDX, CycloneDX, Syft), validate their integrity, and proactively address vulnerabilities within your software ecosystem.
Integration of Utility Data into 3D BIM Models Using a 3D Solids Modeling Wor...
Integration of Utility Data into 3D BIM Models Using a 3D Solids Modeling Wor...Safe Software Jacobs has developed a 3D utility solids modelling workflow to improve the integration of utility data into 3D Building Information Modeling (BIM) environments. This workflow, a collaborative effort between the New Zealand Geospatial Team and the Australian Data Capture Team, employs FME to convert 2D utility data into detailed 3D representations, supporting enhanced spatial analysis and clash detection.
To enable the automation of this process, Jacobs has also developed a survey data standard that standardizes the capture of existing utilities. This standard ensures consistency in data collection, forming the foundation for the subsequent automated validation and modelling steps. The workflow begins with the acquisition of utility survey data, including attributes such as location, depth, diameter, and material of utility assets like pipes and manholes. This data is validated through a custom-built tool that ensures completeness and logical consistency, including checks for proper connectivity between network components. Following validation, the data is processed using an automated modelling tool to generate 3D solids from 2D geometric representations. These solids are then integrated into BIM models to facilitate compatibility with 3D workflows and enable detailed spatial analyses.
The workflow contributes to improved spatial understanding by visualizing the relationships between utilities and other infrastructure elements. The automation of validation and modeling processes ensures consistent and accurate outputs, minimizing errors and increasing workflow efficiency.
This methodology highlights the application of FME in addressing challenges associated with geospatial data transformation and demonstrates its utility in enhancing data integration within BIM frameworks. By enabling accurate 3D representation of utility networks, the workflow supports improved design collaboration and decision-making in complex infrastructure projects
The State of Web3 Industry- Industry Report
The State of Web3 Industry- Industry ReportLiveplex Web3 is poised for mainstream integration by 2030, with decentralized applications potentially reaching billions of users through improved scalability, user-friendly wallets, and regulatory clarity. Many forecasts project trillions of dollars in tokenized assets by 2030 , integration of AI, IoT, and Web3 (e.g. autonomous agents and decentralized physical infrastructure), and the possible emergence of global interoperability standards. Key challenges going forward include ensuring security at scale, preserving decentralization principles under regulatory oversight, and demonstrating tangible consumer value to sustain adoption beyond speculative cycles.
Azure vs AWS Which Cloud Platform Is Best for Your Business in 2025
Azure vs AWS Which Cloud Platform Is Best for Your Business in 2025Infrassist Technologies Pvt. Ltd.
Machine Learning Algorithms | Machine Learning Tutorial | Data Science Tutorial | Edureka
- 1. www.edureka.co/data-scienceEdureka’s Data Science Certification Training
- 2. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Agenda for Today’s Session What is an Algorithm? What is Machine Learning? How is a problem solved using Machine Learning? Types of Machine Learning Machine Learning Algorithms Demo
- 3. www.edureka.co/data-scienceEdureka’s Data Science Certification Training What is an Algorithm?
- 4. www.edureka.co/data-scienceEdureka’s Data Science Certification Training What is an Algorithm? To tell a computer what it has to do, you need a program.
- 5. www.edureka.co/data-scienceEdureka’s Data Science Certification Training What is an Algorithm? To tell a computer what it has to do, you need a program. A program is nothing but logic in some language’s syntax
- 6. www.edureka.co/data-scienceEdureka’s Data Science Certification Training logic What is an Algorithm? To tell a computer what it has to do, you need a program. This logic is what an Algorithm is
- 7. www.edureka.co/data-scienceEdureka’s Data Science Certification Training What is an Algorithm? A process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer
- 8. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Algorithm - Example Start Initialize X = 0 Increment X by 1 Print X X< 20 END NO YES This is a simple algorithm to print numbers from 1 to 20.
- 9. www.edureka.co/data-scienceEdureka’s Data Science Certification Training What is Machine Learning?
- 10. www.edureka.co/data-scienceEdureka’s Data Science Certification Training What is Machine Learning? Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can change when exposed to new data.
- 11. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Machine Learning Types
- 12. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Categories of Algorithms Supervised Learning Reinforcement Learning Unsupervised Learning Types of Learning
- 13. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Supervised Learning Supervised Learning Unsupervised Learning Reinforcement Learning Let’s take an example here. Say you are a teacher, and your way of teaching is, To teach by example, i.e for every problem in their life you are providing solutions to them, this type of learning is called supervised learning. Let’s take the same example forward: Supervised learning is a type of machine learning algorithm that uses a known dataset (called the training dataset) to make predictions. The training dataset includes input data and response values. From it, the supervised learning algorithm seeks to build a model that can make predictions of the response values for a new dataset. Teaching by Example
- 14. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Unsupervised Learning Supervised Learning Unsupervised Learning Reinforcement Learning When your kids are taking decisions out of their own understanding, this type of learning would be Unsupervised Learning. Unsupervised learning is a type of machine learning algorithm used to draw inferences from datasets consisting of input data without labeled responses. Self Learning
- 15. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Reinforcement learning is an area of machine learning inspired by behaviorist psychology, concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward. Reinforcement Learning Supervised Learning Unsupervised Learning Reinforcement Learning If a new situation comes up, the kid will take actions on his own i.e from his past experiences, but as a parent towards the end of an action you can tell him whether he did good or not. Good or Bad?
- 16. www.edureka.co/data-scienceEdureka’s Data Science Certification Training How a problem is solved using Machine Learning?
- 17. www.edureka.co/data-scienceEdureka’s Data Science Certification Training How a problem is solved using Machine Learning? We take a top down approach to answer the same: Classification Algorithm Anomaly Detection Algorithm Regression Algorithms Clustering Algorithms Reinforcement Learning Q1. Q2. Q4. Q3. Q5. Is this A or B? Is this weird? How much or how many? How is this organized? What should I do next? These are the 5 questions which can be answered in data science. These algorithms are fitted into three types of categories, which are the following:
- 18. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Machine Learning Algorithms
- 19. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Classification Algorithms Classification Algorithms are used to classify a record. It is used for questions which can have only a limited number of answers. For Example: When you have only two choices, its called 2 class Classification, if you have more than 2 choices its called Multi Class Classification Is it cold? Will you go to work today? Yes, No or Maybe Yes or No Yes, No or Maybe
- 20. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Anomaly Detection Algorithms It analyzes a certain pattern and alerts you whenever there is change in the pattern. For Example: Anomaly In real life, your credit card company uses these anomaly detection algorithms, and flag any transaction, which is not usual as per your transaction history Did you know? Oh!
- 21. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Regression Algorithms Regression Algorithms are used to calculate numeric values. What will the temperature be tomorrow? How much discount can you give on a particular item? For example:
- 22. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Clustering Algorithms It helps you understand the structure of a dataset. These algorithms separates the data into groups or clusters, to ease out the interpretation of the data. By understanding, how data is organized, you can better predict the behavior of a particular event Group A Group B Group C
- 23. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Reinforcement Algorithms These algorithms were designed as to how brains of humans or rats respond to punishments and rewards, they learn from outcomes, and decide on next action. They are good for systems which have to make lot of small decisions without human guidance. For example: A system which plays chess A temperature control system, when it has to decide whether temperature should be increased or decreased
- 24. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Demo
- 25. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Dataset Training Dataset Testing Dataset A sample dataset to be used is divided like this:
- 26. www.edureka.co/data-scienceEdureka’s Data Science Certification Training Thank You … Questions/Queries/Feedback