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Here’s the book that’s mentioned:


Seems to have good reviews on Amazon:


It's a pretty great general book that I go back to every now and then when I'm reviewing something I'm learning (i.e. GANs) but isn't something I would recommend for newbies to just pick up and try to understanding without at least spending some time learning math/stats since it's a bit more technical than what non-technical might be prepared for.

There's better introductory material out there to Deep Learning, i.e. fast.ai, Ng's Coursera course, Thrun's Udacity's introductory course, tutorials on Medium, where they explain the math/stats behind something but you can get away with learning the process first and play around with code.

Furthermore for some newbies, I think it's a little easier to understand the material when they try to play with it in notebooks (as is the case of books like Hands-On Machine Learning with Sci-Kit Learn and Tensorflow) than trying to just memorize statements on a page.

But certainly for those here who are more technically orientated, it's an excellent book to pore over. I just like to caution friends interested in Deep Learning that it's not the be all, end all way of getting into it and that if someone out there is interested there are more gradual learning curves elsewhere to get their feet wet before committing to trying to go deeper.

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