PDF Ebook , by Arthur Zhang
PDF Ebook , by Arthur Zhang
The , By Arthur Zhang is guide that we now suggest. This is not sort of big book. But, this book will assist you to get to the big idea. When you come to read this book, you can obtain the soft documents of it as well as wait in some various tools. Obviously, it will depend on exactly what device that you own as well as do. For this situation, guide is recommended to conserve in laptop, computer system, or in the device.
, by Arthur Zhang
PDF Ebook , by Arthur Zhang
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Product details
File Size: 470 KB
Print Length: 281 pages
Simultaneous Device Usage: Unlimited
Publication Date: March 8, 2017
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B06XHR9TJC
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Amazon Best Sellers Rank:
#333,029 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
I am not a data scientist or involved in that field in anyway. Big data however is a huge part of the world and it is only getting more important as systems become automated and rely every more on collecting and analyzing large sets of data.I was worried this book might be above my head given that I have no background in data science, or that it would be so dry and academic that it would put me to sleep. I am happy to say that the book was none of hose things.This is a really, really interesting read regardless of your background. The author describes not only the current state of data science, but where it is rapidly headed in the future. Most importantly, everything in the book is grounded in the real world applications of big data that are all around us.This is an interesting, enjoyable, and enlightening read.
I bought this book hoping it could help me to understand a bit more about algorithms and machine learning for a college course on data science. I was not disappointed. This book lays out difficult concepts clearly but without getting too basic or talking down to the reader. It was actually much more helpful than the course textbook in terms of both its clarity and its breadth.I think that regardless of the level you are at in your understanding of data science, this book can help you. I'd recommend it to students, professionals, and casual enthusiasts. An easy five stars.
I read this book right after "Weapons of Math Destruction" and they were both excellent. I was worried this might be too technical for me but even though I have little background in data science I was able to understand pretty much everything. The other really is clear and lucid in his thinking and explanations.My favorite part of the book was about algorithms. More of our lives these days are controlled or influenced by algorithims than ever before and it is important to understand how they work, and more importantly how they DON'T work.
I am sorry, but there is no way that this book could legitimately have a four-star rating. I had high expectations for it based on the table of contents, but after I purchased and started reading it, OMG this is actually the worst book I have ever tried to read. I did not realize that the book was self published. It is double-spaced with narrow margins and so it is really not 270 pages (it's more like 150, maybe). But, more importantly, the book is loaded with spelling, usage, and grammar problems as well as outright errors in the subject matter. The problem with this subject area is that it is so complicated that it makes it difficult for anyone trying to learn something about the subject to find a source that is readable. This book is basic, but it is not readable (unless you are a fan of broken English). This book was obviously not peer reviewed or properly edited. I am actually surprised that Amazon allows anyone to post their book(s) for sale on this Web site. This book does not include an index (for looking up important terms), footnotes, or references (and so the sources of the author's exclamations are unknown). I must admit that I have not read every page of this book. Believe me, I have tried to read as much as possible, but keep having to put it down because the writing is so bad that it just makes me cringe. The text also, in the title, claims to be a practical guide to leveraging the power of algorithms, but I can't find anything in the book about algorithms. Since there is no index, it is not possible to try to find them either. Algorithms are more relevant to machine learning, but this text only mentions machine learning by name and when it does it provide a very confusing description of supervised versus unsupervised learning. Actually, the more I reread the table of contents the more I realize the lack of logic to this book's organization. Bottom line is that this book would be rejected by any legitimate publishing company and is definitely not worth $11.97 as a paperback. Maybe 99 cents as a properly spaced 150-page e-book.
not really a technical or theoretical book
The material was informative but the grammar was a bit of a challenge. Additionally some sections contained repeated sections which were distracting.
An overview at best. Not what I hoped for. Look elsewhere if you want to learn anything about methodologies or how to analyze data.
I recommend this book for learning data science first step.
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