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# Python Libraries This document describes various Python libraries. ## NumPy - A library for the Python programming language. - Adds support for large, multi-dimensional arrays and matrices. - Provides a collection of high-level mathematical functions for these arrays. ## Scikit-learn - A free...

# Python Libraries This document describes various Python libraries. ## NumPy - A library for the Python programming language. - Adds support for large, multi-dimensional arrays and matrices. - Provides a collection of high-level mathematical functions for these arrays. ## Scikit-learn - A free software machine-learning library. - Offers various classification, regression, and clustering algorithms. - Includes support vector machines, random forests, gradient boosting, and k-means. - Designed to work with Python numerical and scientific libraries NumPy and SciPy. ## Pandas - A software library for Python. - Used for data manipulation and analysis. ## Matplotlib - A plotting library for the Python programming language. - Builds upon NumPy's numerical mathematics extension. ## TensorFlow - An open-source software library. - Used for dataflow programming across diverse tasks. ## Keras - An open-source neural network library written in Python. - Can run on top of TensorFlow, Microsoft Cognitive Toolkit, Theano, or MXNet. ## Jupyter - An open-source web application. - Allows creation and sharing of documents containing: - Live code - Equations - Visualizations - Narrative text ## Google Colab - Similar to Jupyter Notebook. - Offers "google doc" type sharing and collaboration features. ## Crestle - A GPU-enabled Jupyter environment in the cloud.