[H862.Ebook] PDF Ebook TensorFlow for Machine Intelligence: A Hands-On Introduction to Learning Algorithms, by Sam Abrahams, Danijar Hafner, Erik Erwitt, Ariel S
PDF Ebook TensorFlow for Machine Intelligence: A Hands-On Introduction to Learning Algorithms, by Sam Abrahams, Danijar Hafner, Erik Erwitt, Ariel S
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TensorFlow for Machine Intelligence: A Hands-On Introduction to Learning Algorithms, by Sam Abrahams, Danijar Hafner, Erik Erwitt, Ariel S
PDF Ebook TensorFlow for Machine Intelligence: A Hands-On Introduction to Learning Algorithms, by Sam Abrahams, Danijar Hafner, Erik Erwitt, Ariel S
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TensorFlow, a popular library for machine learning, embraces the innovation and community-engagement of open source, but has the support, guidance, and stability of a large corporation. Because of its multitude of strengths, TensorFlow is appropriate for individuals and businesses ranging from startups to companies as large as, well, Google. TensorFlow is currently being used for natural language processing, artificial intelligence, computer vision, and predictive analytics. TensorFlow, open sourced to the public by Google in November 2015, was made to be flexible, efficient, extensible, and portable. Computers of any shape and size can run it, from smartphones all the way up to huge computing clusters. This book is for anyone who knows a little machine learning (or not) and who has heard about TensorFlow, but found the documentation too daunting to approach. It introduces the TensorFlow framework and the underlying machine learning concepts that are important to harness machine intelligence. After reading this book, you should have a deep understanding of the core TensorFlow API.
- Sales Rank: #58819 in Books
- Published on: 2016-11-10
- Original language: English
- Dimensions: 9.25" h x .68" w x 7.00" l,
- Binding: Paperback
- 298 pages
Most helpful customer reviews
20 of 22 people found the following review helpful.
Not yet ready, and not that close
By Matt Ginsberg
I originally thought this was a good book. I no longer think that.
It's not a book yet. It will probably be a good book at some point, but that point is not now.
The first few chapters "work". I was able to work through them and everything came out just like it should have. With chapter 5, that completely stopped.
At a high level, what's going on for me is that the examples stopped being self-contained. They don't really tell you where to initialize tf sessions, where to initialize the variables, etc. They just give you code that is supposed to somehow work (but doesn't).
I've spent many hours trying to figure this out. From the point labeled "convert images to TFRecords" and forward, I just can't get anything to happen. I've tried typing everything into python and running it, both with a tensorflow session and without. I've tried running code I downloaded with jupyter and ipython. I just get a bunch of complaints about widgets being unavailable, kernels not existing, and notebooks not being trusted. I've installed a ton of stuff (ipython, jupyter, widgetsnbextension and ipywidgets, for starters) and nothing helps. I've looked at the various manual pages for tensorflow, and that doesn't help, either.
I suspect that if I already knew tensorflow, I would be able to stagger through this. But I don't (that's why I bought the book!), and this book truly isn't helping.
3 of 3 people found the following review helpful.
Good intro but needs an editor.
By Mike Basilyan
The top level summary of my review is: good book, gentle & thorough introduction but wow does it need work and editing. I'm giving it 4 stars because there are few other options out there and the pros outweigh the cons for me.
The good: Overall I found the book to be very accessible and an easy introduction to Tensorflow. It takes its time to explain key TF concepts and how they work in the context of machine learning. Examples are good and accessible.
The bad: Did they forget to proof read the book? On page 96 there's a section called "Logging with TensorBoard" but there's no actual text in that section, just the heading. They keep referring to colors in graphs (blue lines, red dots, etc.) but the book is printed in black and white. There are typos and incomplete sentences everywhere.
0 of 0 people found the following review helpful.
A good introduction
By Decao Mao
I bought this book simply because there was no other choice on the same topic, and I didn't expect too much from the book. But it turns out this is really a good book, much better than I expected, for an introduction to Tensorflow, its principles and its applications. Especially to those who already have some basic understanding on Machine Learning and Dataflow, but need to know what Tenserflow is and how it works, this is a good introduction to start with.
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