First TensorFlow Book is Published!

Man, it has been a while since I posted anything!

I’ve emerged from my writer’s cave (along with my co-authors), and have emerged with TensorFlow for Machine Intelligence! In my extremely biased opinion, it’s one of the best resources out there for people trying to get started with TensorFlow. I had a heavy hand in helping design the content of the book, and I wanted to make sure that learning the software was as digestible as possible. I’m not a huge fan of marketing buzz-speak, but one of our reviewers, Guillaume Binet, says

“Finally a TensorFlow book for humans.”

TensorFlow for Machine Intelligence
The book’s snazzy cover!

Mission Accomplished Sort Of!

I Have no idea how it’s going to sell, but hopefully a decent amount of people find the book helpful. Right now, a huge amount of the reward from this process has been getting even more deeply acquainted with the TensorFlow library. Plus, I can literally say “I wrote the book on it”.

I’ve been working on this with the fine folks at Bleeding Edge Press for several months, and while for a book the timeframe has been pretty short, this release feels like a long time coming.

Special thanks to my awesome co-authors Danijar Hafner, Erik Erwitt, and Ariel Scarpinelli. We had a few tight deadlines, but at the end of the day we’ve got an awesome book!

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TensorFlow White Pages Notes – On GitHub

Hey all!

Huge content in a short post. I just released my TensorFlow white paper notes on GitHub. It’s been a much larger project than I originally thought, but I hope that it will be useful to people. The notes go from the very beginning of the paper all the way through conclusions, highlighting the important information from each section.

Here are the top features of the notes:

  • Notes broken down and organized section by section, as well as subsection by subsection
  • Relevant links to documentation, resources, and references throughout
  • SVG versions of figures/graphs from the paper

If you haven’t checked out the TensorFlow white paper yet, I highly recommend it. There’s no replacement for reading the original, but I hope these notes are a worthy supplement alongside the actual paper.

Next up: Using TensorFlow on transformed Santa Monica Parking data

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