Python Machine Learning-Library- Technology.powerpoint
- 2. The best subject of all the Artificial Intelligence domain is machine learning which has been in the news for quite some time. This field has the potential to provide a better and necessary opportunity. It is very easy to start a career even if you have zero in Mathematics or Programming. Even if you have experience, there is no problem because it is the most important element for your success, purely to help you learn those things. Data for which you have your interest and inspiration. If you are new then you do not know where to start studying and why you need machine learning and why it is gaining the most popularity, then you have come to the right place to get better knowledge from here. I have collected better information and useful resources to help you complete all your projects. Technologies and Tools covered Python Programming language Python packages/libraries Anaconda Navigator Machine Learning algorithms https://uii.io/pyml
- 3. Python is a general-purpose, high level programming language. It was mainly developed for an emphasis on code readability. A great choice of library is one of the main reasons python is the most popular programming language used for AI. Some of the libraries which we used for machine learning are
- 4. NumPY: NumPY stands for Numerical Python. NumPy is used to perform mathemat_x0002_ical operations on Arrays. Various other libraries like Pandas, Matplotlib, and Scikit_x0002_learn are built on top of this amazing library. Pandas: Pandas is a python data analysis library. It is an open- source python library that provides high-performance, easy-to-use data structures and data analysis tools. It is one of the tools used for data cleaning and analysis.
- 5. Matplotlib: Matplotlib is one of the most popular and oldest plotting libraries in Py_x0002_thon which is used in Machine Learning. From histograms to scatterplots, matplotlib lays down an array of colors, themes, palettes, and other options to customize and personalize our plots. Seaborn: Seaborn is a library for making statistical graphics in Python. It builds on top of matplotlib and integrates closely with pandas data structures. Seaborn helps you explore and understand your data.
- 6. Types of Machine learning Supervised Learning: Supervised learning uses a training set to teach models to yield the desired output. This training dataset includes inputs and correct outputs, which allow the model to learn over time. Unsupervised Learning: unsupervised learning uses unlabeled data. This is partic_x0002_ularly useful when subject matter experts are unsure of common properties within a data set.
- 7. Classification Model i. Logistic Regression: Logistic Regression is a supervised classification is unique machine learning algorithm in python that finds its use in estimating discrete values like 0/1, yes/no and true/false. ii. K-Nearest Neighbor: This is a supervised learning algorithm that considers different centroids and uses Euclidean function to compare distance. Then, it analyses the re_x0002_sults and classifies each point to group to optimize it to place with all closest points to it.
- 8. iii. Decision Tree: A decision tree falls under supervised machine learning algorithm in python that comes of use for both classification and regression, although mostly for classification. iv. Random Forest: Random Forest is a popular machine learning algorithm that be_x0002_longs to the supervised learning technique. It can be used for both Classification and Regression problems in ML. I