This is a fine book for its purpose: a very basic introduction to Azure ML / ML Studio. This is not an introduction to machine learning or data mining. Even though the book provides some very basic explanation of the different ML techniques presented in it, you'll get it better of you already understand what the different techniques and algorithms do. And these techniques constitute the basic organization of the book (regression, classification, clustering, recommender systems, and publishing. These chapters are preceded by chapters on introducing ML Studio's browser interface, getting data in and out of there, and the always-essential data preparation stage.
Beyond that, the book requires no preexisting knowledge of coding since Azure ML has a drag-and-drop interface, where you drop modules on a canvas, customize them, connect them together in experiments. Thankfully, the book provides a lot of screenshots of the different procedures it describes and also provides a few "do it yourself" exercises at the end of each chapter, as well as several exercises chapters at the end.
So, this is all very handy, with very few errors (with so many references to modules and models, there's bound to be a few slip-ups here or there). This highlights the convenience and ease of use of Azure ML for a non-technical audience.
Extremely useful for not-entirely beginners. Remember, you have to know some machine learning / data mining if you want to make the best use of this book, which is very clearly written.
Hi recommended especially if coding is not your forte. ( )