Machine Learning: For Beginners – Your Definitive guide For Neural Networks, Algorithms, Random Forests and Decision Trees Made Simple (Machine Learning Series Book 1)

Imagine you went on a date one night, and in order to make small talk you say, "so, what do you do?" (Secretly you're hoping this is the one!)"Oh, I'm a data science/machine learning specialist", he/she replies."Mmm, sounds cool, tell me more!", you follow, expertly hiding your trepidation."Well, machine learning is the study of...blah blah blah...KNN...Regression...Trees and forests!.............."The proceeding chit chat would result in the booklet at hand. And no chance of a second date... So, nope, this is not the one. Your alcoholic mom was right.For an intro to the field, it is pretty bad IMHO. The author touches on all of the major components, but he does so with a heavy handedness reminiscent of freshman year poetry. At times too basic, at times taking leaps and bounds between subjects. For instance, in chapter 2, I believe, he contrives to give us a quick summary of probability theory going from a basic definition of random variables all the way to Bayes theorem. All in 12 pocket-bible sized pages. I guess this is fine if he was expecting the reader to be conversant in the basics of probability, but it defeats the purpose when he fails to meaningfully connect this chapter with the ones that follow.In addition, given the subject is somewhat technical, it would perhaps help the reader to see some figures, maybe a diagram or two. But no, Mr. Gates won't suffer no diagrams. Decisions trees? Nope. Maybe a simple cartesian plane to illustrate KNN? No sir.Oh, and the bad editing and typesetting. In the first two chapters there's repeated sentences, paragraphs, bullet points. And when he does present a formula or some notation, it would have you believe it was done on a type writer, by calculus professor from the 1930's.All in all, it feels rushed and unprepared. I get the sense this book was pulled directly from a powerpoint presentation...Hey! there's an idea for your next date!

I don’t think the author of this book is a real person. I searched the Googles far and wide for an associate university lecturer named Matt Gates with an interest in Machine Learning, heck, even Computer Science. He doesn’t exist.The reason for my search was that this book was just horrible. You don’t need to be an expert in Machine Learning to run your writing through a grammar check, or even have a friend proofread it. This book is riddled with grammatical errors, missing or repeated words, and nonsensical sentences that completely change or distort the meaning of the narrative. Many passages had to be re-read 3 or 4 times to just decipher them as proper English and establish the sentence structure.As for content, this book will *at best* teach you the names of some algorithms to read more about and learn on your own. There is no depth whatsoever, and not even a coherent basic explanation of what any algorithm is or does. Formulas are thrown around willy-nilly without any explanation for what they do or are used for. Certainly not a beginner explanation to be found.The author(s) attempts to give examples in several instances of when or where a specific concept applies. Each time this happened, I said to myself “OK, now we’re getting somewhere, this example looks cool”. And then it completely falls off a cliff with no follow-up or elaboration, and more willy-nilly space-filling formulas. It’s as if he’s writing “Wouldn’t it be cool if you could solve a problem like this with Machine Learning? Well too bad, because I’m not going to tell you how!”My hunch is that someone with a cursory knowledge of Machine Learning put together an outline for this book, then hired cheap writers to regurgitate the main points from some Wikipedia articles.And the worst part is you pay $17 for a book that is more like a pamphlet than anything else and takes a couple hours to read at most.

This book is very odd. The last few pages introduce you to the editorial team, and it was supposedly written by an associate college professor, but I don't think anyone actually proofed the text. Indeed, I am not sure a human even wrote it. Seriously, if you read from the bottom of pg. 6, and go on to pg. 7 (amazon didn't permit me to attach a photo of that text), you will see what I mean. It is the worst writing I've ever seen, and appears to have been generated by some sort of poorly-programmed robot. There are repeated phrases, and other typographical and grammatical errors. After awhile, I just couldn't go on. It was too much work to try to understand the message the author attempted to convey - I sent it back for a full refund of my money.

This book sounded good but I was extremely disappointed when I finally got my hands on it. Not only is it tremendously basic, it doesn't account for the fact that if people order this book they have more than likely heard of some of these terms. So give us more than the term! In addition, I'm not sure the author is familiar with all there is around some of the terms, e.g. neural networks--unstructured learning?! He needs to dig further into neural networks to correctly represent them! Way over-priced book with little value, I am returning.

Too simplistic in the exposition. The book just lists details, sometimes not crucial, while at the same time not providing intuitions