Skip to content

The official code repository for examples in the O'Reilly book 'Generative Deep Learning'

License

Notifications You must be signed in to change notification settings

PFLigthart/GDL_code

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

57 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Generative Deep Learning

Teaching Machines to paint, write, compose and play

The official code repository for examples in the O'Reilly book 'Generative Deep Learning'

https://learning.oreilly.com/library/view/generative-deep-learning/9781492041931/

https://www.amazon.com/Generative-Deep-Learning-Teaching-Machines/dp/1492041947/ref=sr_1_1

Tensorflow

This branch uses standalone Keras with a Tensorflow 1.14 backend. See the tensorflow_2 branch for the Keras within Tensorflow 2.0 version of the codebase.

Structure

This repository is structured as follows:

The notebooks for each chapter are in the root of the repository, prefixed with the chapter number.

The data folder is where to download relevant data sources (chapter 3 onwards) The run folder stores output from the generative models (chapter 3 onwards) The utils folder stores useful functions that are sourced by the main notebooks

Book Contents

Part 1: Introduction to Generative Deep Learning

  • Chapter 1: Generative Modeling
  • Chapter 2: Deep Learning
  • Chapter 3: Variational Autoencoders
  • Chapter 4: Generative Adversarial Networks

Part 2: Teaching Machines to Paint, Write, Compose and Play

  • Chapter 5: Paint
  • Chapter 6: Write
  • Chapter 7: Compose
  • Chapter 8: Play
  • Chapter 9: The Future of Generative Modeling
  • Chapter 10: Conclusion

Getting started

To get started, first install the required libraries inside a virtual environment:

pip install -r requirements.txt

About

The official code repository for examples in the O'Reilly book 'Generative Deep Learning'

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 95.2%
  • Python 4.7%
  • Shell 0.1%