If you want to build multiple neural network architectures such as CNN, RNN, LSTM in Keras, we recommend you to read Neural Networks with Keras Cookbook by V Kishore Ayyadevara. We recommend the full podcast that’s available on Fridman’s YouTube channel. In this post, we have tried to highlight François’ views on the Keras and TensorFlow 2.0 integration, early days of Keras and the importance of design decisions for building deep learning models. In September, Lex Fridman, Research scientist at MIT popularly known for his podcasts, spoke to François Chollet, who is the author of Keras on Keras, Deep Learning, and the Progress of AI.
It serves as an interface to several deep learning libraries, most popular of which is TensorFlow, and it was integrated into TensorFlow main codebase in TensorFlow 2.0. Keras is an open-source deep-learning library that is designed to enable fast, user-friendly experimentation with deep neural networks. One of the major highlights of this release was the integration of Keras into TensorFlow. TensorFlow 2.0 was made available in October.
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