Top 10 Python Libraries for Machine Learning

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  1. Pandas

    Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

    Website: https://pandas.pydata.org/ Github Repository: https://github.com/pandas-dev/pandas Developed By: Community Developed (Originally Authored by Wes McKinney) Primary Purpose: Data Analysis and Manipulation

  2. InfluxDB

    InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.

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  3. OpenCV

    Open Source Computer Vision Library

    Website: https://opencv.org/ Github Repository: https://github.com/opencv/opencv Developed By: initially by Intel Corporation Primary purpose: Only focuses on Computer Vision OpenCV

  4. tensorflow

    An Open Source Machine Learning Framework for Everyone

    Website: https://www.tensorflow.org/ GitHub Repository: https://github.com/tensorflow/tensorflow Developed By: Google Brain Team Primary Purpose: Deep Neural Networks

  5. examples

    TensorFlow examples (by tensorflow)

    Website: https://www.tensorflow.org/ GitHub Repository: https://github.com/tensorflow/tensorflow Developed By: Google Brain Team Primary Purpose: Deep Neural Networks

  6. NumPy

    The fundamental package for scientific computing with Python.

    Website: https://numpy.org/ Github Repository: https://github.com/numpy/numpy Developed By: Community Project (originally authored by Travis Oliphant) Primary purpose: General Purpose Array Processing

  7. scikit-learn

    scikit-learn: machine learning in Python

    Website: https://scikit-learn.org/ Github Repository: https://github.com/scikit-learn/scikit-learn Developed By: SkLearn.org Primary Purpose: Predictive Data Analysis and Data Modeling

  8. NLTK

    NLTK Source

    Website: https://www.nltk.org/ Github Repository:https://github.com/nltk/nltk Developed By: Team NLTK Primary Purpose: Natural Language Processing

  9. SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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  10. Pytorch

    Tensors and Dynamic neural networks in Python with strong GPU acceleration

    Website: https://pytorch.org/ Github Repository: https://github.com/pytorch/pytorch Developed By: Facebook AI Research lab (FAIR) Primary purpose: Deep learning, Natural language Processing, and Computer Vision

  11. Keras

    Deep Learning for humans

    Website: https://keras.io/ Github Repository: https://github.com/keras-team/keras Developed By: various Developers, initially by Francois Chollet Primary purpose: Focused on Neural Networks

  12. mlpack

    mlpack: a fast, header-only C++ machine learning library

    Github Repository: https://github.com/mlpack/mlpack Developed By: Community, supported by Georgia Institute of technology Primary purpose: Multiple ML Models and Algorithms

  13. cheatsheets

    Official Matplotlib cheat sheets (by matplotlib)

    Website: https://matplotlib.org/ Github Repository: https://github.com/matplotlib/matplotlib Developed By: Micheal Droettboom, Community Primary purpose: Data Visualization

  14. matplotlib

    matplotlib: plotting with Python

    Website: https://matplotlib.org/ Github Repository: https://github.com/matplotlib/matplotlib Developed By: Micheal Droettboom, Community Primary purpose: Data Visualization

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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