/keras-idiomatic-programmer

Handbooks and Code Samples for Software Engineers wanting to learn the Keras Machine Learning framework

Primary LanguageJupyter NotebookOtherNOASSERTION

License License

Idiomatic Programmer

This repository contains the handbooks in softcopy (PDF) and code examples from the Idiomatic Programmer handbook series, as well as presentation packs and accompanying code labs. The Idiomatic Programmer materials are produced by Google AI Developer Relations. The audience for the materials are software engineers wanting to learn machine learning. Our first series focuses on the Keras framework and computer vision, along with OpenCV.

The material has been designed both for self-learning, and for being incorporating into instructional material for universities, private coding schools, and professional training. Licensed as Apache 2.0 and CC-BY, organizations are free to integrate and customize the material into their curriculum.

The repository is organized by:

Directory Description
src code snippets for handbooks (e.g., handbook1) - Apache 2.0 license
handbooks PDF softcopy of handbooks - CC-BY 4.0 license
Primer - Statistics Fundamentals for Machine Learning
Handbook 1 - Learning Keras - Computer Vision Models
Handbook 2 - Learning Keras (OpenCV) - Computer Vision Data Engineering
Handbook 3 - Learning Keras - Computer Vision Training and Deployment
workshops workshops (presentation slides and code labs) - CC-BY 4.0 license
Neural Networks
Convolutional Neural Networks
Wide Convolutional Neural Networks
Advanced Neural Networks
Mobile Networks
Data Engineering
Data Augmentation
Training
Transfer Learning
Production
notebooks notebooks for production-grade solutions
zoo tf.keras model zoo (coded in idiomatic programming style) - Apache 2.0 license

Reviewers

We thank the following for their reviews and contributions to the Idiomatic Programmer:

Google Cloud AI - Developer Relations

Andrew Ferlitsch
Noah Negrey
Yu-Han Liu
Shahin Saadati
Torry Yang
Gonzalo Gasca Meza
Amy Unruh
Martin Groner
Brad Miro
Tianzi Cai

Google Developer Experts (GDE)

Margaret Maynard-Reid / Seattle

ML Practioners

Hobson Lane
Enoch Tetteh

Disclaimer

This is not an officially supported Google product.