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Amazon verified reviews

Verified Amazon Customer Jul 22, 2017

Excellent book. It contains lots of practical examples. However, when I copied the codes from the book, there were some alignment issues and some codes were not executed correctly. Therefore, I had to manually fixed them.Fortunately, the authors have fixed all the minor bugs and the updated codes that I have downloaded from GitHub/Deep-Learning-with-TensorFlow are working perfectly.

Amazon Verified review

Ambuj Jan 07, 2018

Good introduction if you want to start with tensor flow

Matthew R. Versaggi Jan 03, 2018

I had such high hopes for this book - the theory is OK, but this is supposed to be a practitioners book with code that actually works and is of Tensorflor 1.X whereas there is lots of code pre-tensorflow 1.x in the code base which generate difficult errors to debug.I'm in Ch 3 and scrapping the book for something else. Sad.Update:I have seen improvements in Ch4 with CNN's the code is cleaner and the explanation is improving.

Barry Hart Jun 30, 2017

Much of the book seems like a rehash or even direct quotes from the TensorFlow Dev Summit put on by Google in early 2017. If you've watched the videos, this book might serve as a good set of notes. The book doesn't have much flow or unity. If you're looking to learn TensorFlow from scratch, I recommend Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems instead.

Dimitri Shvorob Mar 12, 2018

Wishing to learn about TensorFlow, I decided to survey TF books available from Amazon, and pick one or two for further study. I excluded self-published offerings, and ended up with this longish list, dominated by Packt titles:"Machine Learning with TensorFlow" by Shukla, published by Manning in 2018-02, 272 pp, $43"Mastering TensorFlow 1.x" by Fandango, Packt, 2018-01, 474 pp, $35"Pro Deep Learning with TensorFlow" by Pattanayak, Apress, 2017-12, 398 pp, $37"TensorFlow 1.x Deep Learning Cookbook" by Gulli and Kapoor, Packt, 2017-12, 536 pp, $32"Neural Network Programming with TensorFlow" by Ghotra and Dua, Packt, 2017-11, 274 pp, $40"Predictive Analytics with TensorFlow" by Karim, Packt, 2017-11, 522 pp, $50"Machine Learning with TensorFlow 1.x" by Hua and Azeem, Packt, 2017-11, 304 pp, $39"Learning TensorFlow" by Hope and Resheff, O'Reilly, 2017-08, 242 pp, $25"Hands-On Deep Learning with TensorFlow" by Van Boxel, Packt, 2017-07, 174 pp, $35"Deep Learning with TensorFlow" by Zaccone, Karim, Menshawy, Packt, 2017-04, 320 pp, $50"TensorFlow Machine Learning Cookbook" by McClure, Packt, 2017-02, 370 pp, $30"Building Machine Learning Projects with TensorFlow" by Bonnin, Packt, 2016-11, 291 pp, $35"Getting Started with TensorFlow" by Zaccone, Packt, 2016-07, 180 pp, $35I reviewed the doc on tensorflow.org - including the doc for older releases - then started looking at books. One week later, I am still not done, but have winnowed out some options. The books by Van Boxel and Zaccone are out - these are brief (and not up-to-date) introductions, costing as much as more substantial titles - and the book by Karim is "disqualified" for blatant plagiarism.What happens when Messrs Zaccone and Karim collaborate? It seems that the former continues to do honest work, and the latter continues to pilfer content. I am reading an electronic copy and cannot point to page numbers, but a chunk of "Neural networks as computational graphs" Section in Chapter 1 seems to be purloined from Brandon Brown of Outlace.com (see post "On chain rule, computational graphs, and back-propagation"), and Chapter 10, "Reinforcement learning", is taken without attribution from Arthur Juliani. Sorry, I have to stop here, give one star and move on. It's a pity, because "Deep Learning with TensorFlow" has substance - as copy-pastes go, this is a fairly wide-ranging, and undeniably enriched, copy-paste - but plagiarism should not be encouraged.

Deep Learning with TensorFlow: Explore neural networks with Python

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