Deep Learning With Python: Develop Deep Learning Models on Theano and TensorFlow Using Keras

by Jason Brownlee

Deep learning is the most interesting and powerful machine learning technique right now. Top deep learning libraries are available on the Python ecosystem like Theano and TensorFlow. Tap into their power in a few lines of code using Keras, the best-of-breed applied deep learning library. Discover exactly how to get started and apply deep learning to your own machine learning projects.

Genres: Computer Science

256 pages, ebook

Published January 1, 2016

About the author

Jason Brownlee, Ph.D. trained and worked as a research scientist and software engineer for many years (e.g. enterprise, R&D, and scientific computing), and is known online for his work on Computational Intelligence (e.g. Clever Algorithms), Machine Learning and Deep Learning (e.g. Machine Learning Mastery, sold in 2021) and Python Concurrency (e.g. Super Fast Python).

Jason writes fiction under the pseudonym J.D. Brownlee: https://www.goodreads.com/jdbrownlee

Reviews

[Johannes · Rating 2 out of 5]

Brownlee's books are usually very good, but this one is rather riddled with shallow explanations and offers little development of technical intuition. Get the book with the same title by Francois Chollet instead. It's more detailed, more comprehensive, and gives a better conceptual and technical understanding.

[Ankit Tyagi · Rating 3 out of 5]

Mostly what I get from this book is clean code. It looks more like a code book than a deep learning book. Theory is almost negligible with no very less visualization. I would recommend this book only as a reference for writing codes otherwise go for some other book for deep learning.

[Souna · Rating 4 out of 5]

It was really very helpful for me.
straight to the point with end to end projects.
I highly recommend it

[Ibrar · Rating 2 out of 5]

Its good book

[Akash Nidhi P S · Rating 4 out of 5]

Its a very good book for beginner with basic knowledge of Python , numpy, pandas and concepts of CNN and RNN.

[Jeevan]

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