Just in case you didn’t hear, the long-awaited TensorFlow 2.0 was officially released on September 30th.

And while it’s certainly a time for celebration, many deep learning practitioners such as Jeremiah are scratching their heads:

— What does the TensorFlow 2.0 release mean for me as a Keras user?
— Am I supposed to use the keras package for training my own neural networks?
— Or should I be using the tf.keras submodule inside TensorFlow 2.0 instead?
— Are there TensorFlow 2.0 features that I should care about as a Keras user?

The transition from TensorFlow 1.x to TensorFlow 2.0 is going to be a bit of a rocky one, at least to start, but with the right understanding, you’ll be able to navigate the migration with ease. Read More

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