Keras is a popular, open-source deep learning API for Python built on top of TensorFlow and is useful for fast implementation. Topics include efficient low-level tensor operations, computation of arbitrary gradients, scalable computations, export of graphs, etc.
What is Keras?
Keras is a popular, open-source deep learning API for Python built on top of TensorFlow and is useful for fast implementation. Topics include efficient low-level tensor operations, computation of arbitrary gradients, scalable computations, export of graphs, etc.
New to Keras?
There are various resources including books, tutorials/workshops, etc. for those looking to learn how to use Keras.
Introductions on the Keras website:
Introduction to Keras for Engineers
Introduction to Keras for Researchers
A popular introductory book is:
Deep Learning with Python, by François Chollet.
keras Tag usage
When posting questions about Keras, please take the following into consideration:
When tagging questions with the keras tag, users should make sure to post sufficient information regarding model construction (layers, input shape, activation functions, etc.) and include all other relevant tags that pertain to the specific topic at hand.
Explicit programming related questions are more suitable for Stack Overflow and should not be posted on Stack Exchange Data Science.
Questions should include sufficient details and clarity to be able to provide support for the problem at hand. This includes linking to underlying data used, providing code used for the model's construction, highlighting relevant outputs, etc.
External Resources
Keras: Documentation Page
Important Links
Issue Tracker: https://github.com/keras-team/keras/issues
