They did id!
Guys at Sitepoint released Machine Learning eBook which is compilation of content from their ML course for free so everyone can download it!
Download Sitepoint Machine Learning Ebook for free
So what’s good inside? Let’s take a look at book contest.
It’s preface tells us that it’s beginner-friendly and its goal is to shinine a torch across the landscape of machine learning.
First chapter funnily named “Become a Machine Learning Learning Machine” introduces us to concept of Machine Learning and shows how to spot whenever particular technique used by someone somewhere is real, legit Machine Learning or only something similar advertised as ML to get more clicks.
Chapter no 2 “Algorithm and Blues” introduces Machine Learning algorithms. At this point it also becomes apparent what this book really is - it’s just curated collection of link to places (sites/ articles/ tutorials) that will cover the current topic in detail and/ or teach you how to do something.
Third chapter “Present Tense: TensorFlow” (funny chapter name once again) presents tool most used presently in the world of Machine Learning: open-source machine learning network TensorFlow. In this chapter you’ll learn what TensorFlow is, its quirks and finally start coding Machine Learning. Two best covered programming languages are Ruby and R, but you’ll also learn about TensorFlowOnSpark which is is a Yahoo effort to establish distributed xiv A Deep Dive into Machine Learning TensorFlow with Apache Spark (don’t get upset if you can’t really follow all of this at this point).
Next chapter starts with interesting saying: “There’s a universal law in development: if something exists, someone has made a JavaScript version of it.” I don’t know if it’s always true, but in this instance it is, hence the chapter title reads “TensorFlow.js and Machine Learning with JavaScript”.
5th chapter “Solid Snake: Machine Learning with Python” (MGS anyone?) pairs ML with one of the most popular programming language of these days.
Similarly, 6th chapter shows options for Lua programmers wanting to start with Machine Learning.
Following chapters dives deeper, showing you how could you utilize ML in real life applications: we’ll see offers from companies like Microsoft, Google, Amazon and IBM covered.
Last two chapters are for iOS and Android developers and show what options these ecosystems offer when it comes to ML.