Python in Action: Machine Learning

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

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  • examples

    TensorFlow examples (by tensorflow)

  • 6. TensorFlow is an open-source machine learning platform. In addition to providing robust libraries for machine learning in Python, it includes a range of tools and user resources that facilitate highly portable machine learning models.

  • seaborn

    Statistical data visualization in Python

  • 5. Seaborn is built on Matplotlib and can be used for plotting statistics and generating accessible graphics.

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • 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

  • 3. Pandas is another open-source library. It provides a range of tools for data analysis and manipulation, and it’s frequently used in conjunction with NumPy, SciPy, and Matplotlib.

  • NumPy

    The fundamental package for scientific computing with Python.

  • 1. NumPy is an open source Python library that’s used for complicated mathematical operations. It’s compatible with some of the other libraries listed below such as Pandas, Matplotlib, and Scikit-learn.

  • cheatsheets

    Official Matplotlib cheat sheets (by matplotlib)

  • 4. Matplotlib is the most popular Python library for data visualization and 2-D plotting.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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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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