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Getting started /
Learning resources
Learning resources
This page is a compilation of learning resources for modern Keras best practices.
Notes that best starter resources are still our developer guides, our official code examples, as well as the tutorials on tensorflow.org.
If this is your first contact with Keras, you can also check out the guides Introduction to Keras for researchers and Introduction to Keras for engineers.
Books
- Deep Learning with Python (second edition), by François Chollet - Code examples available on GitHub
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (second edition), by Aurélien Géron
- Practical Machine Learning for Computer Vision, by Valliappa Lakshmanan, Martin Görner, Ryan Gillard
- Practical Deep Learning for Cloud, Mobile, and Edge, by Anirudh Koul, Siddha Ganju, and Meher Kasam
- Deep Learning for Computer Vision with Python, by Adrian Rosebrock
MOOCs
- TensorFlow in Practice specialization on Coursera
- Getting started with TensorFlow 2 on Coursera, by Imperial College London