Machine Learning Tools and Algorithms

This page summarizes the projects mentioned and recommended in the original post on reddit.com/r/u_Snoo36930

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  • examples

    TensorFlow examples (by tensorflow)

    TensorFlow:-TensorFlow is the most widely used neural network. In 2015, Google released TensorFlow, an open-source framework that was created by the company. Thousands of businesses, startups, and industry organizations are increasingly relying on TensorFlow to streamline operations and build cutting-edge solutions. TensorFlow provides APIs that are both high-level and low-level in nature.

  • Apache Spark

    Apache Spark - A unified analytics engine for large-scale data processing

    Apache Spark :- A massive data processing engine with built-in modules for streaming, SQL, Machine Learning (ML), and graph processing, Apache Spark is recognized for being quick, simple to use, and general. It is also known for being fast, simple to use, and generic.

  • Scout APM

    Truly a developer’s best friend. Scout APM is great for developers who want to find and fix performance issues in their applications. With Scout, we'll take care of the bugs so you can focus on building great things 🚀.

  • Pytorch

    Tensors and Dynamic neural networks in Python with strong GPU acceleration

    PyTorch :- It is one of the most widely used machine learning methods, and it is employed in some of the most significant fields of machine learning, such as the construction of deep neural networks and the computation of tensors.

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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