Est. read time: 1 minute | Last updated: December 17, 2024 by John Gentile


Contents

Overview

It is useful to review linear algebra concepts before continuing.

TBD reference [1]

Intro ML

Software and Platforms

TensorFlow

TensorFlow is one of the most popular platforms for Machine Learning development, protoyping and deployment.

TensorFlow Docker Container with GPU Support

Follow instructions at python-lib/tensorflow to install a Docker container with NVIDIA CUDA GPU support and common Jupyter & SciPy libraries.

TensorFlow Development

Open In Colab

Other TensorFlow Resources

PyTorch

Jupyter Notebooks

For more info, see SciPy distribution in Python about installing Jupyter notebook support.

Another great tool which comes with most all dependencies/libraries ready to go is Google Colab, which allows you to store (in Google Drive), edit and run (even on GPU & TPU servers in some instances) Jupyter notebooks in the Google cloud environment.

Other Tools

  • Horovod: Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet
  • MLPerf: ML benchmark results for various computing platforms.
  • Caffe 2 is now a part of PyTorch

References

  1. [1]I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning. MIT Press, 2016 [Online]. Available at: http://www.deeplearningbook.org