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T**
More than an Introduction to Machine Learning
I recommend this book to my students because it fills a gap among the many machine learning textbooks. Alpaydin provides a great exposition of the key algorithms and theories behind supervised, unsupervised, and reinforcement learning in a concise manner. Most of the textbooks focus on how to program in Python or R. Alpaydin discusses the foundations of key machine learning models to be effective in programming and understanding the outcomes. The author also revised the deep learning section with new material on Generative Adversarial Networks, Convolutional Neural Network, among others. This book is a great resource.
A**R
great book for machine learning theory and concept
This book is easy to read, and the author explains the theory and concept in a very simple English.
S**I
Fun read
Starts off a bit technical/math heavy but slowly becomes more practice over theory.
A**R
Good but not colored
Good content. Short and precise. It is not colored.
J**A
Received book with chapter 1 not included
The book I received was a misprint that did not include the 1st chapter of the book. Book begins on page 25 after the title page
S**E
Not a very easy to go approach
Well, although this book got some really detailed theoretical background for supervised/unsupervised techniques, this book requires a sufficient background in theoretical/statistical mathematics. For someone completely new to machine learning who needs some excitement to grow his / her interest. this book might not be a great start.
C**J
This book has the wrong name; it's awful in that sense
This book is 2/5 but I'm giving it a 1/5 because of it inflated reviews. Do not read this as your first Machine Learning book if you are not already a trained statistician; and as a second book, there are superior alternatives. The grand issue with this book is that it's red like a recipe.I despise the writing style that the author is using; he introduces completely new concepts without any whatsoever explanation. He never ever explains "why", he just presents formulas and throw around terms. Most of the algorithms are way better and more intuitively explained through Wikipedia. Fortunately, I'm already familiar with most of the topics but I'm astonished that the course I'm studying chose such an obnoxious book.Do not buy
P**N
good book, reasonable price
I'm a statistician and usually think machine learning books are simplistic and misleading. This is an exception. The treatment is thorough, better than most.
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