- My choice has fallen to a presentation by François Chollet of the deep learning library API Keras and its integration with TensorFlow.
- As Dr. Chollet explains, Keras integrated with TensorFlow promises to streamline deep learning frameworks in ways that will be increasingly user-friendly, rendering the mass adoption of these software developments a more feasible reality:
Dr. François Chollet is the primary author of Keras, developing this tool while at Research at Google.

- For instance the way video with text data is processed with the Keras-TensorFlow integration is nicely described with the stack of CNNs, LSTMs and dense final layers with softmax being features explained by Dr. Chollet.
- The best practises advised by Dr. Chollet about the initialization of recurrent weighs of the neural network is worth to listen, even if the experienced practitioner feels bored.
- A final note to the confirmation by Dr. Chollet of the capacity of TensorFlow to streamline a CloudML or a hyperparameter tuning process with just a few lines of code, enabling a distributed training platform able to enhance big data computes with productivity gains.

I am briefly sharing a video from the last TensorFlow Dev Summit in February 2017. My choice has fallen to a presentation by François Chollet of the deep learning library API Keras and its integration with TensorFlow. As Dr. Chollet explains, Keras integrated with TensorFlow promises to streamline deep learning frameworks in ways that will…

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