This post is adapted from Section 2 of Chapter 9 of my book, Deep Learning with Python (Manning Publications). It is part of a series of two posts on the current limitations of deep learning, and its future. This post is targeted at people who already have significant experience with deep learning (e.g. people who have read chapters 1 through 8 of the book). We assume a lot of pre-existing knowled
This post is adapted from Section 3 of Chapter 9 of my book, Deep Learning with Python (Manning Publications). It is part of a series of two posts on the current limitations of deep learning, and its future. You can read the first part here: The Limitations of Deep Learning. Given what we know of how deep nets work, of their limitations, and of the current state of the research landscape, can we p
Note: this post is from April 2016. It no longer reflects TensorFlow and Keras best practices. Keras has now been integrated into TensorFlow. Please see the keras.io documentation for details. A complete guide to using Keras as part of a TensorFlow workflow If TensorFlow is your primary framework, and you are looking for a simple & high-level model definition interface to make your life easier, th
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