This document provides an overview of the Python programming language, including its history, key features, syntax examples, and common uses. It also discusses how Python can be used under Linux and some potential issues.
Practical Natural Language Processing From Theory to Industrial Applications Jaganadh Gopinadhan
The document provides an overview of a presentation on practical natural language processing (NLP). It discusses Jaganadh G, an expert in NLP, machine learning, and data mining who is giving the presentation. The presentation covers introducing NLP and its goals, discussing practical NLP problems and solutions, explaining NLP tasks like text classification and information extraction, and exploring topics such as morphology, part-of-speech tagging, and syntactic parsing. The goal is to discuss both theory and real-world applications of NLP.
First-order logic (FOL) is a formal system used in mathematics, philosophy, linguistics, and computer science to represent knowledge about domains involving objects and relations. FOL extends propositional logic with quantifiers and predicates to describe properties of and relations between objects. Well-formed formulas in FOL involve constants, variables, functions, predicates, quantifiers, and logical connectives. The meaning and truth of FOL statements is determined with respect to a structure called a model that specifies a domain of objects and interpretations of symbols. FOL can be used to represent knowledge about many different domains and perform logical inference.
The document describes pushdown automata (PDA). A PDA has a tape, stack, finite control, and transition function. It accepts or rejects strings by reading symbols on the tape, pushing/popping symbols on the stack, and changing state according to the transition function. The transition function defines the possible moves of the PDA based on the current state, tape symbol, and stack symbol. If the PDA halts in a final state with an empty stack, the string is accepted. PDAs can recognize any context-free language. Examples are given of PDAs for specific languages.
This document summarizes key topics in intermediate code generation discussed in Chapter 6, including:
1) Variants of syntax trees like DAGs are introduced to share common subexpressions. Three-address code is also discussed where each instruction has at most three operands.
2) Type checking and type expressions are covered, along with translating expressions and statements to three-address code. Control flow statements like if/else are also translated using techniques like backpatching.
3) Backpatching allows symbolic labels in conditional jumps to be resolved by a later pass that inserts actual addresses, avoiding an extra pass. This and other control flow translation topics are covered.
The document provides an overview of the A* pathfinding algorithm. It begins by defining the pathfinding problem and describing applications like game development. It then introduces the A* algorithm, which finds the shortest path between nodes in a graph by considering both the distance traveled so far (like in Dijkstra's algorithm) and the estimated distance to the goal (like in best-first search). The document provides an example of A* in action and discusses how heuristics can guide the search while ensuring an optimal solution. It also compares the running time of A* to Dijkstra's algorithm.
The document discusses tombstone diagrams, which use puzzle pieces to represent language processors and programs. It then explains bootstrapping, which refers to using a compiler to compile itself. This allows obtaining a compiler for a new target machine by first writing a compiler in a high-level language, compiling it on the original machine, and then using the output compiler to compile itself on the new target machine. The document provides examples of using bootstrapping to generate cross-compilers that run on one machine but produce code for another.
Prolog is a declarative logic programming language where programs consist of facts and rules. Facts are terms that are always true, while rules define relationships between terms using logic notation "if-then". A Prolog program is run by asking queries of the program's database. Variables must start with an uppercase letter and are used to represent unknown values, while atoms are constants that represent known values.
Introduction to Machine Learning with Find-SKnoldus Inc.
Machine Learning with Find-S algorithm. 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.
The document describes rules for constructing the First and Follow sets for a context-free grammar. It provides an example grammar and shows the step-by-step application of the rules to derive the First and Follow sets for each nonterminal symbol in the grammar.
GPU computing provides a way to access the power of massively parallel graphics processing units (GPUs) for general purpose computing. GPUs contain over 100 processing cores and can achieve over 500 gigaflops of performance. The CUDA programming model allows programmers to leverage this parallelism by executing compute kernels on the GPU from their existing C/C++ applications. This approach democratizes parallel computing by making highly parallel systems accessible through inexpensive GPUs in personal computers and workstations. Researchers can now explore manycore architectures and parallel algorithms using GPUs as a platform.
Entropy and information gain in decision tree.Megha Sharma
Entropy is a measure of unpredictability or impurity in a data set. It is used in decision trees to determine the best way to split data at each node. High entropy means low purity with an equal mix of classes, while low entropy means high purity with mostly one class. Information gain is the reduction in entropy when splitting on an attribute, with the attribute with the highest information gain chosen as the split. For example, in a data set on restaurant patrons, splitting on the "patrons" attribute results in a higher information gain than splitting on "type of food" so "patrons" would be chosen as the root node.
Sets are collections of unique elements that do not allow repetition. Elements must satisfy membership rules to be included in a set. Common set operations include union, intersection, difference and subset testing. Sets can be mutable, allowing addition and removal of elements, or immutable. Hash functions are used to map elements to locations in hash tables, enabling fast set operations on large collections. Spelling checkers use hash tables to implement sets and check dictionary words against input words.
Machine Translation (MT) refers to the use of computers for the task of translating
automatically from one language to another. The differences between languages and
especially the inherent ambiguity of language make MT a very difficult problem. Traditional
approaches to MT have relied on humans supplying linguistic knowledge in the form of rules
to transform text in one language to another. Given the vastness of language, this is a highly
knowledge intensive task. Statistical MT is a radically different approach that automatically
acquires knowledge from large amounts of training data. This knowledge, which is typically
in the form of probabilities of various language features, is used to guide the translation
process. This report provides an overview of MT techniques, and looks in detail at the basic
statistical model.
Fuzzy logic is a method of reasoning that resembles human decision making by allowing for intermediate possibilities between yes and no or true and false. It is used in control systems like temperature controllers, anti-lock braking systems, washing machines, and air conditioners. Fuzzy logic applications can be found in areas like aerospace, automotive, defense, electronics, mining, robotics, securities, and industrial processes. The field of fuzzy logic continues to grow and provide opportunities to develop effective controllers for complex systems across many domains.
The document discusses different types of logical reasoning systems used in artificial intelligence, including knowledge-based agents, first-order logic, higher-order logic, goal-based agents, knowledge engineering, and description logics. It provides examples of objects, properties, relations, and functions that can be represented and reasoned about logically. It also compares different approaches to logical indexing and outlines the key components and inference tasks involved in description logics.
The document discusses recursion and lists in Prolog. It covers recursive definitions, clause ordering and termination, lists, members, and recursing down lists. Recursive definitions allow a predicate to refer to itself in its own definition. Clause ordering can impact termination and procedural meaning. Lists are a fundamental recursive data structure in Prolog, consisting of elements separated by commas and enclosed in brackets. The member predicate checks if an element is in a list by recursively working down the list. Recursing down lists is common for tasks like comparing lists or copying elements between lists.
Top Python Project Ideas for Beginners in 2024.pdfAhana Sharma
The document lists several beginner Python project ideas including a to-do list app that allows adding, editing, and deleting tasks, a weather app that fetches live data to display temperature, humidity and forecasts, a basic web scraper to extract information from websites, a number guessing game where the player tries to guess a random number selected by the computer, a currency converter that fetches live exchange rates to convert between currencies, and a digital recipe book to add, edit and view recipes.
The document discusses minimizing finite automata by removing unnecessary states. It defines when two states are indistinguishable versus distinguishable. It then describes the procedure to mark all pairs of distinguishable states and group indistinguishable states together. Finally, it outlines the reduce procedure to create a minimized automaton by replacing groups of indistinguishable states with single merged states and updating the transitions accordingly. The goal is to find the smallest equivalent automaton that accepts the same language.
Prolog focuses on describing facts and relationships about problems rather than steps to solve problems. It uses facts to work out solutions by searching possible solutions. Facts are declared with a predicate followed by objects in parentheses separated by commas. Rules are used when a fact depends on other facts, with the head before the body separated by ":-". Variables begin with capital letters and are used to represent unknown values. Conjunction uses commas to represent "AND" and disjunction uses semicolons to represent "OR" between predicates.
Consensus algorithms allow distributed systems to agree on common values despite potential failures. Paxos is a consensus algorithm that allows a group of processes to agree on a single value among them despite potential process failures or lost messages. It works by having one process designated as the leader to propose values and other processes vote on those values to decide on a common value.
Theory of automata and formal languageRabia Khalid
The document discusses theory of automata and formal languages. It defines key concepts like abstract machines, automata, alphabets, strings, words, languages and provides examples to describe them. Abstract machines are theoretical models of computer systems used to analyze how they work. Automata are self-operating machines that follow predetermined sequences of operations. Alphabets are sets of symbols, strings are concatenations of symbols, and words are strings belonging to a language. Languages can be defined descriptively or recursively and examples are given to illustrate different ways of defining languages.
Using Machine Learning and Chatbots to handle 1st line Technical SupportBarbara Fusinska
This document discusses using machine learning and chatbots to handle first line technical support. It begins with an introduction to the speaker and agenda. It then provides an overview of what chatbots are, including definitions and examples. Common uses of chatbots for customer service and technical support are described. The typical architecture of a chatbot is outlined. Popular chatbot platforms are listed. An example use case of an "IT Crowd Answering Machine" chatbot is demonstrated. The document discusses using natural language processing and classification models to apply artificial intelligence to chatbots. It shows how this can be done using tools like LUIS and the Bot Framework. Challenges of training chatbots and correctly classifying user inputs are also mentioned.
The document outlines the 5 phases of natural language processing (NLP):
1. Morphological analysis breaks text into paragraphs, sentences, words and assigns parts of speech.
2. Syntactic analysis checks grammar and parses sentences.
3. Semantic analysis focuses on literal word and phrase meanings.
4. Discourse integration considers the effect of previous sentences on current ones.
5. Pragmatic analysis discovers intended effects by applying cooperative dialogue rules.
This document provides a summary of Dhruv Bhasin's industrial training report on web development using SharePoint Server 2013 at Adobe Systems India Private Limited. It includes an introduction, objectives of the training, formal training provided on SharePoint, and sessions on key SharePoint concepts like sites, lists, libraries, social networking features, and integrating SharePoint with Office applications. The training aimed to develop practical skills in web development and provided theoretical and hands-on lessons on administering and developing on the SharePoint platform.
Regular expressions-Theory of computationBipul Roy Bpl
Regular expressions are a notation used to specify formal languages by defining patterns over strings. They are declarative and can describe the same languages as finite automata. Regular expressions are composed of operators for union, concatenation, and Kleene closure and can be converted to equivalent non-deterministic finite automata and vice versa. They also have an algebraic structure with laws governing how expressions combine and simplify.
From the perspective of Design and Analysis of Algorithm. I made these slide by collecting data from many sites.
I am Danish Javed. Student of BSCS Hons. at ITU Information Technology University Lahore, Punjab, Pakistan.
The document discusses Python generators and how they can be used for iterating over lists, tuples, dictionaries, strings, files and custom iterable objects. It provides examples of using generators and the yield keyword to iterate over a countdown and generate values. The document also discusses two problems - analyzing log files using generators and finding files matching patterns using the os.walk generator.
Introduction to Machine Learning with Find-SKnoldus Inc.
Machine Learning with Find-S algorithm. 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.
The document describes rules for constructing the First and Follow sets for a context-free grammar. It provides an example grammar and shows the step-by-step application of the rules to derive the First and Follow sets for each nonterminal symbol in the grammar.
GPU computing provides a way to access the power of massively parallel graphics processing units (GPUs) for general purpose computing. GPUs contain over 100 processing cores and can achieve over 500 gigaflops of performance. The CUDA programming model allows programmers to leverage this parallelism by executing compute kernels on the GPU from their existing C/C++ applications. This approach democratizes parallel computing by making highly parallel systems accessible through inexpensive GPUs in personal computers and workstations. Researchers can now explore manycore architectures and parallel algorithms using GPUs as a platform.
Entropy and information gain in decision tree.Megha Sharma
Entropy is a measure of unpredictability or impurity in a data set. It is used in decision trees to determine the best way to split data at each node. High entropy means low purity with an equal mix of classes, while low entropy means high purity with mostly one class. Information gain is the reduction in entropy when splitting on an attribute, with the attribute with the highest information gain chosen as the split. For example, in a data set on restaurant patrons, splitting on the "patrons" attribute results in a higher information gain than splitting on "type of food" so "patrons" would be chosen as the root node.
Sets are collections of unique elements that do not allow repetition. Elements must satisfy membership rules to be included in a set. Common set operations include union, intersection, difference and subset testing. Sets can be mutable, allowing addition and removal of elements, or immutable. Hash functions are used to map elements to locations in hash tables, enabling fast set operations on large collections. Spelling checkers use hash tables to implement sets and check dictionary words against input words.
Machine Translation (MT) refers to the use of computers for the task of translating
automatically from one language to another. The differences between languages and
especially the inherent ambiguity of language make MT a very difficult problem. Traditional
approaches to MT have relied on humans supplying linguistic knowledge in the form of rules
to transform text in one language to another. Given the vastness of language, this is a highly
knowledge intensive task. Statistical MT is a radically different approach that automatically
acquires knowledge from large amounts of training data. This knowledge, which is typically
in the form of probabilities of various language features, is used to guide the translation
process. This report provides an overview of MT techniques, and looks in detail at the basic
statistical model.
Fuzzy logic is a method of reasoning that resembles human decision making by allowing for intermediate possibilities between yes and no or true and false. It is used in control systems like temperature controllers, anti-lock braking systems, washing machines, and air conditioners. Fuzzy logic applications can be found in areas like aerospace, automotive, defense, electronics, mining, robotics, securities, and industrial processes. The field of fuzzy logic continues to grow and provide opportunities to develop effective controllers for complex systems across many domains.
The document discusses different types of logical reasoning systems used in artificial intelligence, including knowledge-based agents, first-order logic, higher-order logic, goal-based agents, knowledge engineering, and description logics. It provides examples of objects, properties, relations, and functions that can be represented and reasoned about logically. It also compares different approaches to logical indexing and outlines the key components and inference tasks involved in description logics.
The document discusses recursion and lists in Prolog. It covers recursive definitions, clause ordering and termination, lists, members, and recursing down lists. Recursive definitions allow a predicate to refer to itself in its own definition. Clause ordering can impact termination and procedural meaning. Lists are a fundamental recursive data structure in Prolog, consisting of elements separated by commas and enclosed in brackets. The member predicate checks if an element is in a list by recursively working down the list. Recursing down lists is common for tasks like comparing lists or copying elements between lists.
Top Python Project Ideas for Beginners in 2024.pdfAhana Sharma
The document lists several beginner Python project ideas including a to-do list app that allows adding, editing, and deleting tasks, a weather app that fetches live data to display temperature, humidity and forecasts, a basic web scraper to extract information from websites, a number guessing game where the player tries to guess a random number selected by the computer, a currency converter that fetches live exchange rates to convert between currencies, and a digital recipe book to add, edit and view recipes.
The document discusses minimizing finite automata by removing unnecessary states. It defines when two states are indistinguishable versus distinguishable. It then describes the procedure to mark all pairs of distinguishable states and group indistinguishable states together. Finally, it outlines the reduce procedure to create a minimized automaton by replacing groups of indistinguishable states with single merged states and updating the transitions accordingly. The goal is to find the smallest equivalent automaton that accepts the same language.
Prolog focuses on describing facts and relationships about problems rather than steps to solve problems. It uses facts to work out solutions by searching possible solutions. Facts are declared with a predicate followed by objects in parentheses separated by commas. Rules are used when a fact depends on other facts, with the head before the body separated by ":-". Variables begin with capital letters and are used to represent unknown values. Conjunction uses commas to represent "AND" and disjunction uses semicolons to represent "OR" between predicates.
Consensus algorithms allow distributed systems to agree on common values despite potential failures. Paxos is a consensus algorithm that allows a group of processes to agree on a single value among them despite potential process failures or lost messages. It works by having one process designated as the leader to propose values and other processes vote on those values to decide on a common value.
Theory of automata and formal languageRabia Khalid
The document discusses theory of automata and formal languages. It defines key concepts like abstract machines, automata, alphabets, strings, words, languages and provides examples to describe them. Abstract machines are theoretical models of computer systems used to analyze how they work. Automata are self-operating machines that follow predetermined sequences of operations. Alphabets are sets of symbols, strings are concatenations of symbols, and words are strings belonging to a language. Languages can be defined descriptively or recursively and examples are given to illustrate different ways of defining languages.
Using Machine Learning and Chatbots to handle 1st line Technical SupportBarbara Fusinska
This document discusses using machine learning and chatbots to handle first line technical support. It begins with an introduction to the speaker and agenda. It then provides an overview of what chatbots are, including definitions and examples. Common uses of chatbots for customer service and technical support are described. The typical architecture of a chatbot is outlined. Popular chatbot platforms are listed. An example use case of an "IT Crowd Answering Machine" chatbot is demonstrated. The document discusses using natural language processing and classification models to apply artificial intelligence to chatbots. It shows how this can be done using tools like LUIS and the Bot Framework. Challenges of training chatbots and correctly classifying user inputs are also mentioned.
The document outlines the 5 phases of natural language processing (NLP):
1. Morphological analysis breaks text into paragraphs, sentences, words and assigns parts of speech.
2. Syntactic analysis checks grammar and parses sentences.
3. Semantic analysis focuses on literal word and phrase meanings.
4. Discourse integration considers the effect of previous sentences on current ones.
5. Pragmatic analysis discovers intended effects by applying cooperative dialogue rules.
This document provides a summary of Dhruv Bhasin's industrial training report on web development using SharePoint Server 2013 at Adobe Systems India Private Limited. It includes an introduction, objectives of the training, formal training provided on SharePoint, and sessions on key SharePoint concepts like sites, lists, libraries, social networking features, and integrating SharePoint with Office applications. The training aimed to develop practical skills in web development and provided theoretical and hands-on lessons on administering and developing on the SharePoint platform.
Regular expressions-Theory of computationBipul Roy Bpl
Regular expressions are a notation used to specify formal languages by defining patterns over strings. They are declarative and can describe the same languages as finite automata. Regular expressions are composed of operators for union, concatenation, and Kleene closure and can be converted to equivalent non-deterministic finite automata and vice versa. They also have an algebraic structure with laws governing how expressions combine and simplify.
From the perspective of Design and Analysis of Algorithm. I made these slide by collecting data from many sites.
I am Danish Javed. Student of BSCS Hons. at ITU Information Technology University Lahore, Punjab, Pakistan.
The document discusses Python generators and how they can be used for iterating over lists, tuples, dictionaries, strings, files and custom iterable objects. It provides examples of using generators and the yield keyword to iterate over a countdown and generate values. The document also discusses two problems - analyzing log files using generators and finding files matching patterns using the os.walk generator.
Server Administration in Python with Fabric, Cuisine and WatchdogConFoo
This document discusses tools for managing servers remotely using Python: Fabric allows interacting with remote machines as if they were local, Cuisine automates server configuration tasks like installing packages and config files, and Watchdog ensures servers and services stay running. The presentation promotes these tools for streamlining server deployment and administration across multiple servers located in different data centers or with different providers.
Este documento discute las opciones para integrar código C++ con Python. Explica que Python es útil para productividad mientras que C++ es mejor para desempeño. Presenta opciones como Python/C API, Cython, SWIG y Boost para crear interfaces entre los lenguajes. Recomienda que SWIG es popular pero que Boost es mejor para ambientes C++, aunque requiere más conocimiento de C++. Finalmente, enfatiza que Python y C++ pueden trabajar juntos de forma efectiva.
Introduction to the rapid prototyping with python and linux for embedded systemsNaohiko Shimizu
This document outlines a workshop on embedded Linux rapid prototyping using the Raspberry Pi. The workshop agenda includes preparing the Raspberry Pi, embedded Linux programming with C, and rapid prototyping with Python. The objective is to browse embedded system development, learn Linux API basics, create kernel modules, and do rapid prototyping with Python. Participants will install software, set up cross-compilation tools, access GPIO pins from C programs, and handle interrupts from device drivers.
The document discusses using Chef to deploy Django applications to real-world infrastructures. It begins by introducing Chef and its main components, including resources, recipes, roles, and treating infrastructure as code. It then covers using Python-specific tools with Chef and provides a case study on Packaginator, a Python packaging tool.
This document discusses automated deployment using Fabric, a tool that streamlines SSH for application deployment. Fabric allows deploying code to multiple servers with less code than shell scripts and less mistakes than manual deployment. It demonstrates shutting down Tomcat, backing up files, uploading new code, and restarting Tomcat on remote servers with one command. Fabric installation and configuration are also covered, along with its APIs and how it saves time through one step deployment compared to manual processes.
O documento apresenta uma palestra sobre o uso de Python e Qt5 em sistemas embarcados Linux. É discutido como ambas as tecnologias podem ser usadas para desenvolvimento de interfaces gráficas e aplicações em sistemas embarcados usando o framework Yocto Project. Exemplos de aplicações são mostrados rodando em uma plataforma embarcada chamada A.R.O.S.
This document provides an overview of Python for Unix and Linux System Administration by Noah Gift and Jeremy M. Jones. It includes information about related O'Reilly titles, conferences, and online resources from O'Reilly such as oreilly.com and oreillynet.com. It also discusses the Safari Bookshelf online reference library and upcoming O'Reilly conferences.
The document discusses using Fabric for deployment and system administration tasks across multiple servers. It provides examples of Fabric configuration, defining roles for servers, writing tasks to run commands on servers, and how to structure tasks for a full deployment workflow. Fabric allows running commands remotely via SSH and provides tools for task composition and failure handling.
Este documento describe las ventajas de usar Vim como editor de texto y como instalar y usar el plugin Python-mode para Vim. Explica las diferencias entre IDEs y editores de texto, las características clave de Vim como la edición modal y su alta personalización, y proporciona una demostración de Python-mode. También incluye enlaces a recursos adicionales para aprender Vim y encontrar plugins útiles.
Z shell (zsh) provides many powerful features out of the box that can make the shell experience more efficient and productive compared to other shells like bash. Zsh includes advanced tab completion for commands like git, path expansion and replacement, right-hand prompts, spelling correction, powerful aliases, extended globbing, environment variable editing, and programmable file renaming. It also features intuitive history searching, syntax highlighting, and integration with the oh-my-zsh framework. Overall, zsh's extensive capabilities and customization options allow users to optimize their shell workflow.
This document provides an introduction to the Python programming language. It discusses what Python is, its history and creator, why it is popular, who uses it, and how to get started with the syntax. Key topics covered include Python's readability, dynamic typing, standard library, and use across many industries. The document also includes code examples demonstrating basic Python concepts like variables, strings, control flow, functions, and file input/output.
This file contains the first steps any beginner can take as he/she starts a journey into the rich and beautiful world of Python programming. From basics such as variables to data types and recursions, this document touches briefly on these concepts. It is not, by any means, an exhaustive guide to learn Python, but it serves as a good starting point and motivation.
Python is an interpreted, object-oriented programming language created by Guido van Rossum in 1990. It has a clear, readable syntax and is used for rapid prototyping, scripting, web development and more. Key features of Python include its clean syntax, extensive standard library, readability, extensibility via C/C++, and emphasis on code readability and maintenance through use of whitespace and comments.
Python is an object-oriented programming language created by Guido van Rossum in 1990. It is designed to be highly readable and easy to learn. Key features include clean syntax, extensive standard libraries, support for multiple programming paradigms like object-oriented, procedural, and functional programming. Python can be used for tasks like scripting, rapid application development, and web development.
The document provides an overview of the basics of the Python programming language. It discusses that Python is an interpreted, interactive, object-oriented scripting language. It also covers Python's history and describes it as being easy to learn and read, easy to maintain, portable, and extensible. The document then details Python's core data types including numbers, strings, lists, tuples, and dictionaries. It provides examples of how to define and manipulate variables of each data type in Python.
The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists
Python is a simple yet powerful programming language that can be used for a wide range of tasks. The document provides an introduction to Python, discussing why it is a good language to learn, its history and examples of common uses. It covers Python's syntax, data types, modules, object oriented programming and how to interface Python with databases and other languages. The goal is to illustrate Python's versatility and ease of use through examples.
Python is an interpreted, object-oriented programming language created by Guido van Rossum in 1990. It has a clear, readable syntax and is designed to be highly extensible. Python code is often much shorter than equivalent code in other languages like C++ or Java due to features like indentation-based blocks and dynamic typing. It is used for web development, scientific computing, and more.
This document provides an overview of the Python programming language, including its history, key features, and common uses. It discusses how Python is an interpreted, object-oriented language with dynamic typing and automatic memory management. Examples are given of Python's syntax for numbers, strings, modules, data structures like lists and dictionaries, and the interactive shell. Popular applications of Python like web development, science, and games are also mentioned.
The document provides an introduction to the Python programming language, outlining its key features such as being dynamically typed, object oriented, scalable, extensible, portable, and readable. It describes Python's syntax differences from C-style languages and covers basic Python concepts like variables, data types, operators, strings, comments, control flow, functions, modules and packages. The document is intended to help new Python programmers get an overview of the language.
This document outlines the syllabus for a Python programming course. It covers 4 chapters: an introduction to Python, control statements, lists, functions, tuples and dictionaries, sets, modules, files, and exception handling. The introduction discusses Python's history and features. It also covers basic Python concepts like data types, variables, operators, and input/output. Subsequent chapters go into more depth on control flow, data structures, functions, modules and files, exceptions, and assignments include basics, strings, functions, files and dates. The course aims to teach students core Python programming concepts and skills.
Python is a high-level programming language that emphasizes code readability. It has a clear syntax and large standard library. Python can be used for system programming, GUIs, internet scripting, database programming, and more. Some key strengths of Python include being object-oriented, free, portable, powerful, easy to use and learn. Popular uses of Python include web development, scientific computing, and financial applications. The document provides an overview of Python fundamentals like data types, control flow statements, functions, classes, and modules.
This tutorial provides an introduction to the Python programming language. It will cover Python's core features like syntax, data types, operators, conditional and loop execution, functions, modules and packages to enable writing basic programs. The tutorial is intended for learners to learn Python together through questions, discussions and pointing out mistakes.
This document provides an introduction to the Python programming language. It discusses that Python is an interpreted, object-oriented language created by Guido van Rossum in 1990. It then covers Python's core features like being free and open source, rapid prototyping, portability, powerful standard libraries, and more. The document also summarizes Python's basic data types, control structures like if/else statements and loops, functions, file handling, classes and inheritance.
This document is a summer training report submitted by Shubham Yadav to the Department of Information Technology at Rajkiya Engineering College. The report details Shubham's 4-week training program at IQRA Software Technologies where he learned about Python programming language and its libraries like NumPy, Matplotlib, Pandas, and OpenCV. The report includes sections on the history of Python, its characteristics, data structures in Python, file handling, and how to use various Python libraries for tasks like mathematical operations, data visualization, data analysis, and computer vision.
This document provides an overview of the Python programming language. It discusses Python's history and design, data types like integers, floats, strings, lists, tuples and dictionaries. It also covers core concepts like variables, expressions, control flow with if/else statements and loops. The document demonstrates how to take user input, read and write files, and describes moving Python code to files to make it reusable.
This document provides an overview of the Python programming language. It begins with an introduction to running Python code and output. It then covers Python's basic data types like integers, floats, strings, lists, tuples and dictionaries. The document explains input and file I/O in Python as well as common control structures like if/else statements, while loops and for loops. It also discusses functions as first-class objects in Python that can be defined and passed as parameters. The document provides examples of higher-order functions like map, filter and reduce. Finally, it notes that functions can be defined inside other functions in Python.
Python strings are sequences of characters that can be accessed and manipulated using various string methods. Strings can be declared using either single or double quotes and support escape characters. Strings are immutable and concatenation creates a new string. Common string methods include len() to get the length, lower()/upper() to case conversion, strip() to remove whitespace, and startswith()/endswith() to check substrings.
Down the Rabbit Hole – Solving 5 Training RoadblocksRustici Software
Feeling stuck in the Matrix of your training technologies? You’re not alone. Managing your training catalog, wrangling LMSs and delivering content across different tools and audiences can feel like dodging digital bullets. At some point, you hit a fork in the road: Keep patching things up as issues pop up… or follow the rabbit hole to the root of the problems.
Good news, we’ve already been down that rabbit hole. Peter Overton and Cameron Gray of Rustici Software are here to share what we found. In this webinar, we’ll break down 5 training roadblocks in delivery and management and show you how they’re easier to fix than you might think.
Mastering AI Workflows with FME - Peak of Data & AI 2025Safe Software
Harness the full potential of AI with FME: From creating high-quality training data to optimizing models and utilizing results, FME supports every step of your AI workflow. Seamlessly integrate a wide range of models, including those for data enhancement, forecasting, image and object recognition, and large language models. Customize AI models to meet your exact needs with FME’s powerful tools for training, optimization, and seamless integration
Your startup on AWS - How to architect and maintain a Lean and Mean accountangelo60207
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.
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
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
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
AI Agents in Logistics and Supply Chain Applications Benefits and ImplementationChristine Shepherd
AI agents are reshaping logistics and supply chain operations by enabling automation, predictive insights, and real-time decision-making across key functions such as demand forecasting, inventory management, procurement, transportation, and warehouse operations. Powered by technologies like machine learning, NLP, computer vision, and robotic process automation, these agents deliver significant benefits including cost reduction, improved efficiency, greater visibility, and enhanced adaptability to market changes. While practical use cases show measurable gains in areas like dynamic routing and real-time inventory tracking, successful implementation requires careful integration with existing systems, quality data, and strategic scaling. Despite challenges such as data integration and change management, AI agents offer a strong competitive edge, with widespread industry adoption expected by 2025.
Interested in leveling up your JavaScript skills? Join us for our Introduction to TypeScript workshop.
Learn how TypeScript can improve your code with dynamic typing, better tooling, and cleaner architecture. Whether you're a beginner or have some experience with JavaScript, this session will give you a solid foundation in TypeScript and how to integrate it into your projects.
Workshop content:
- What is TypeScript?
- What is the problem with JavaScript?
- Why TypeScript is the solution
- Coding demo
Creating an Accessible Future-How AI-powered Accessibility Testing is Shaping...Impelsys Inc.
Web accessibility is a fundamental principle that strives to make the internet inclusive for all. According to the World Health Organization, over a billion people worldwide live with some form of disability. These individuals face significant challenges when navigating the digital landscape, making the quest for accessible web content more critical than ever.
Enter Artificial Intelligence (AI), a technological marvel with the potential to reshape the way we approach web accessibility. AI offers innovative solutions that can automate processes, enhance user experiences, and ultimately revolutionize web accessibility. In this blog post, we’ll explore how AI is making waves in the world of web accessibility.
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
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.
No-Code Workflows for CAD & 3D Data: Scaling AI-Driven InfrastructureSafe Software
When projects depend on fast, reliable spatial data, every minute counts.
AI Clearing needed a faster way to handle complex spatial data from drone surveys, CAD designs and 3D project models across construction sites. With FME Form, they built no-code workflows to clean, convert, integrate, and validate dozens of data formats – cutting analysis time from 5 hours to just 30 minutes.
Join us, our partner Globema, and customer AI Clearing to see how they:
-Automate processing of 2D, 3D, drone, spatial, and non-spatial data
-Analyze construction progress 10x faster and with fewer errors
-Handle diverse formats like DWG, KML, SHP, and PDF with ease
-Scale their workflows for international projects in solar, roads, and pipelines
If you work with complex data, join us to learn how to optimize your own processes and transform your results with FME.
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.
מכונת קנטים המתאימה לנגריות קטנות או גדולות (כמכונת גיבוי).
מדביקה קנטים מגליל או פסים, עד עובי קנט – 3 מ"מ ועובי חומר עד 40 מ"מ. בקר ממוחשב המתריע על תקלות, ומנועים מאסיביים תעשייתיים כמו במכונות הגדולות.
Boosting MySQL with Vector Search -THE VECTOR SEARCH CONFERENCE 2025 .pdfAlkin Tezuysal
As the demand for vector databases and Generative AI continues to rise, integrating vector storage and search capabilities into traditional databases has become increasingly important. This session introduces the *MyVector Plugin*, a project that brings native vector storage and similarity search to MySQL. Unlike PostgreSQL, which offers interfaces for adding new data types and index methods, MySQL lacks such extensibility. However, by utilizing MySQL's server component plugin and UDF, the *MyVector Plugin* successfully adds a fully functional vector search feature within the existing MySQL + InnoDB infrastructure, eliminating the need for a separate vector database. The session explains the technical aspects of integrating vector support into MySQL, the challenges posed by its architecture, and real-world use cases that showcase the advantages of combining vector search with MySQL's robust features. Attendees will leave with practical insights on how to add vector search capabilities to their MySQL systems.
Enabling BIM / GIS integrations with Other Systems with FMESafe Software
Jacobs has successfully utilized FME to tackle the complexities of integrating diverse data sources in a confidential $1 billion campus improvement project. The project aimed to create a comprehensive digital twin by merging Building Information Modeling (BIM) data, Construction Operations Building Information Exchange (COBie) data, and various other data sources into a unified Geographic Information System (GIS) platform. The challenge lay in the disparate nature of these data sources, which were siloed and incompatible with each other, hindering efficient data management and decision-making processes.
To address this, Jacobs leveraged FME to automate the extraction, transformation, and loading (ETL) of data between ArcGIS Indoors and IBM Maximo. This process ensured accurate transfer of maintainable asset and work order data, creating a comprehensive 2D and 3D representation of the campus for Facility Management. FME's server capabilities enabled real-time updates and synchronization between ArcGIS Indoors and Maximo, facilitating automatic updates of asset information and work orders. Additionally, Survey123 forms allowed field personnel to capture and submit data directly from their mobile devices, triggering FME workflows via webhooks for real-time data updates. This seamless integration has significantly enhanced data management, improved decision-making processes, and ensured data consistency across the project lifecycle.
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!
19. has interfaces to many system calls and libraries, as well as to various window systems, and is extensible in C or C++.
20. usable as an extension language for applications that need a programmable interface.
21. What is Python ??? supports multiple programming paradigms (primarily object oriented, imperative, and functional)
22. portable: runs on many Unix variants, on the Mac, and on PCs under MS-DOS, Windows, Windows NT, OS/2, FreeBSD Solaris, OS/2, Amiga,AROS, AS/400, BeOS, OS/390, z/OS, Palm OS, QNX, VMS, Psion, Acorn RISC OS, VxWorks, PlayStation, Sharp Zaurus, Windows CE and even PocketPC !
23. What is Python ??? Developed and supported by a large team of volunteers - Python Software Foundation
37. Free and open source Implemented under an open source license. Freely usable and distributable, even for commercial use. Simplicity , Great first language
63. E.g. Projects with Python Websites: Google, YouTube, Yahoo Groups & Maps, CIA.gov Appengine: http://code.google.com/appengine/
64. ” Google: Python has been an important part of Google since the beginning.”, Peter Norvig.
65. Python application servers and Python scripting to create the web UI for BigTable (their database project) Systems: NASA, LALN, CERN, Rackspace Nasa Nebula http://nebula.nasa.gov/about Games: Civilization 4, Quark (Quake Army Knife)
87. Strings: format() >>>age = 25 >>>name = 'Swaroop' >>> print ( '{0} is {1} years old' .format(name, age)) Swaroop is 25 years old >>> '{0:.3}' .format( 1 / 3 ) '0.333' >>> '{0:_^11}' .format( 'hello' ) '___hello___' >>> '{name} wrote {book}' .format(name= 'Swaroop' , book= 'A Byte of Python' ) 'Swaroop wrote A Byte of Python'
88. Variables Naming identifiers: The first character be a letter of the alphabet (uppercase ASCII or lowercase ASCII or Unicode character) or an underscore ('_').
89. The rest of the identifier name can consist of letters (uppercase ASCII or lowercase ASCII or Unicode character), underscores ('_') or digits (0-9).
90. Identifier names are case-sensitive. For example, myname and myName are not the same.
92. Indentation Python uses whitespace to determine blocks of code def greet (person): if person == “Tim”: print (“Hello Master”) else : print (“Hello {name}”.format(name=person))
93. Control Flow if guess == number: #do something elif guess < number: #do something else else : #do something else while True : #do something #break when done break else : #do something when the loop ends for i in range( 1 , 5 ): print (i) else : print ( 'The for loop is over' ) #1,2,3,4 for i in range( 1 , 5 , 2 ): print (i) else : print ( 'The for loop is over' ) #1,3
100. Functions Variable length args acceptable as a list or dict def total (initial= 5 , *numbers, **keywords): count = initial for number in numbers: count += number for key in keywords: count += keywords[key] return count print (total( 10 , 1 , 2 , 3 , vegetables= 50 , fruits= 100 ))
101. Functions def printMax (x, y): '''Prints the maximum of two numbers. The two values must be integers.''' x = int(x) # convert to integers, if possible y = int(y) if x > y: r eturn x else : r eturn y printMax( 3 , 5 )
103. Modules can be imported or run by themselves if __name__ == '__main__' : print ( 'This program is being run by itself' ) else : print ( 'I am being imported from another module' )
104. Modules #!/usr/bin/python # Filename: mymodule_demo.py import mymodule mymodule.sayhi() print ( 'Version' , mymodule.__version__) #!/usr/bin/python # Filename: mymodule.py def sayhi (): print ( 'Hi, this is mymodule speaking.' ) __version__ = '0.1' # End of mymodule.py
105. OOP class MyClass : """This is a docstring.""" name = "Eric" def say (self): return ( 'My name is {0}' .format(name)) instance = MyClass() print instance.say()
106. OOP class Person : def __init__ (self, name): self.name = name def __del__ (self): print ( 'deleting this person' ,self.name) def sayHi (self): print ( 'Hello, my name is' , self.name) p = Person( 'Swaroop' ) p.sayHi() del p
107. OOP All class members (including the data members) are public and all the methods are virtual in Python.
111. Files myString = ”This is a test string” f = open( 'test.txt' , 'w' ) # open for 'w'riting f.write(myString) # write text to file f.close() # close the file f = open( 'test.txt' ) #read mode while True : line = f.readline() if len(line) == 0 : # Zero length indicates EOF break print (line, end= '' ) f.close() # close the file
112. Pickle import pickle shoplistfile = 'shoplist.data' shoplist = [ 'apple' , 'mango' , 'carrot' ] f = open(shoplistfile, 'wb' ) pickle.dump(shoplist, f) # dump the object to a file f.close() del shoplist # destroy the shoplist variable f = open(shoplistfile, 'rb' ) storedlist = pickle.load(f) # load the object from the file print (storedlist)
122. Various editors Text editors, IDLE , plugins for eclipse & Netbeans Embeddable in many applications as scripting interface Rhythmbox, Blender, OpenOffice, BitTorrent, ...
123. Linux and Python ” Talk is cheap. Show me the code.” Linus Torvalds