It's been a while since my last ML in JS post, but to make it up to you I'm excited to announce the release of my latest book, Hands-on Machine Learning with JavaScript.
The book is similar in many ways to my old blog series. It's a no-nonsense tour of twenty or so machine learning algorithms, covering many typical use-cases. You learn to write many of the algorithms from scratch, though now that JS has a bit of an ML ecosystem we also use popular libraries (like TensorFlow.js) for the more complex algorithms. I show you the math where necessary, though I focus more on the implementations and the practical advice you'll need when starting to work with ML algorithms.
If you're primarily a JavaScript developer who hasn't worked much with ML, I think you'll love the book. I wrote it specifically for you: experienced JS devs who want to start with machine learning. Even if JS isn't your primary language, you might still love it because you'll learn a lot about ML in the context of a language you're comfortable with. The concepts and lessons in the book are broad enough to apply to any programming language, so you can take it with you when you're done.
If you've enjoyed my blog posts about ML in JS - and I'm proud to say that over a million readers have - please do check out Hands-on Machine Learning with JavaScript.
Teaching is a passion of mine, and I'm always looking for new ways to do it. While I love what I've been able to do with this blog, I think that ML in JS in book form is the right way to present the right material to the right people. I hope you agree, and thanks for being a reader!
