Deep Learning: A Practitioner's Approach

You're right, it is August 2017. I bought it from Amazon UK and they list the date as November 2015 [1] for some reason. I should have checked the book before posting. I've flagged the error with Amazon UK.

[1] https://www.amazon.co.uk/Deep-Learning-Practitioners-Adam-Gi...

For those wondering, why the heck are you guys java:

Our tensor library has a python interface in the making: https://www.slideshare.net/agibsonccc/strata-beijing-2017-ju...

Our goal with this will be then to write side by side benchmarks with the other libs that people can easily run. We know a lot of folks from python land won't jump over and we don't expect them to. The hope is that we're equivalent and can integrate better with a big data cluster.

Dl4j is not trying to be TF. When I started dl4j 4 years ago, it was theano and torch as the primary frameworks.

I wrote it for deployment in to production apps and for the hadoop/spark ecosystem.

We will continue that going forward at the eclipse foundation as well as using dl4j in our product.

Please check out the oreilly book as well (currently #2 on amazon right next to the goodfellow book):

https://amazon.com/Deep-Learning-Practitioners-Josh-Patterso...

Email in profile if there's any specific questions.

Disclaimer: I wrote this deep learning book. My book covers quite a bit of this: https://www.amazon.com/Deep-Learning-Practitioners-Josh-Patt...

It's the least mathy book you'll find and doesn't really assume any math knowledge. Much of it is more focused on production.