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Fundamentals of Deep Learning

This repository is the code companion to Fundamentals of Deep Learning by Nikhil Buduma and Nicholas Locascio. Contributions to the text and code have also been made by Mostafa Samir, Surya Bhupatiraju, and Anish Athalye. All algorithms are implemented in Tensorflow, Google's machine intelligence library.

Guide to the repository

Due to recent changes in the Tensorflow library, specifically the migration to the 1.0 API version, the original code in this repository requires an update. If you are running a pre 1.0 version of Tensorflow, the original code files are contained in the archive/ folder of this repository. We are now beginning the process of migrating this repository into the 1.0 version of Tensorflow and re-organizing the examples. This work is currently in progress and can be found in the fdl_examples/ folder. The current state of the migration is summarized here:

  • Chapter 3
    • Logistic regression (MNIST)
    • Multilayer perceptron (MNIST)
  • Chapter 4
    • Linear interpolation of MLP network (MNIST)
  • Chapter 5
  • Chapter 6
  • Chapter 7
  • Chapter 8
  • Chapter 9

Setting up your development environment

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