In this tutorial we will discover the difference between Keras and tf.keras (tf - TensorFlow), including what’s new in TensorFlow 2.0. By Adrian Rosebrock.
Understanding the complicated, intertwined relationship between Keras and TensorFlow is like listening to the love story of two high school sweethearts who start dating, break up, and eventually find their way together — it’s long, detailed, and at some points even contradictory.
Article also discusses some of the most popular TensorFlow 2.0 features you should care about as a Keras user, including:
- Sessions and eager execution
- Automatic differentiation
- Model and layer subclassing
- Better multi-GPU/distributed training support
… and much more. Code examples, charts and further resources all provided. Excellent!
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