Why do many data scientist use C++ for machine learning?

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

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  • Pytorch

    Tensors and Dynamic neural networks in Python with strong GPU acceleration

    For example, there is PyTorch which is primarily C++ but has Python bindings. Most people use the Python bindings, same for TensorFlow. JAX is mostly Python, same for scikit-learn.

  • tensorflow

    An Open Source Machine Learning Framework for Everyone

    For example, there is PyTorch which is primarily C++ but has Python bindings. Most people use the Python bindings, same for TensorFlow. JAX is mostly Python, same for scikit-learn.

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    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 🚀.

  • jax

    Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

    For example, there is PyTorch which is primarily C++ but has Python bindings. Most people use the Python bindings, same for TensorFlow. JAX is mostly Python, same for scikit-learn.

  • scikit-learn

    scikit-learn: machine learning in Python

    For example, there is PyTorch which is primarily C++ but has Python bindings. Most people use the Python bindings, same for TensorFlow. JAX is mostly Python, same for scikit-learn.

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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