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John W. Foreman

Data Smart: Using Data Science to Transform Information into Insight (英語) ペーパーバック – 2013/11/12

John W. Foreman (著)

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Data Science gets thrown around in the press like it's magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.

But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.

Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet.

Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype.

But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.

Each chapter will cover a different technique in a spreadsheet so you can follow along:

Mathematical optimization, including non-linear programming and genetic algorithms
Clustering via k-means, spherical k-means, and graph modularity
Data mining in graphs, such as outlier detection
Supervised AI through logistic regression, ensemble models, and bag-of-words models
Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation
Moving from spreadsheets into the R programming language

You get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

本の長さ

432ページ
言語

英語
出版社

Wiley
発売日

2013/11/12
寸法

18.54 x 2.03 x 23.11 cm
ISBN-10

111866146X
ISBN-13

978-1118661468
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著者について

John W. Foreman is Chief Data Scientist for MailChimp.com, where he leads a data science product development effort called the Email Genome Project. As an analytics consultant, John has created data science solutions for The Coca-Cola Company, Royal Caribbean International, Intercontinental Hotels Group, Dell, the Department of Defense, the IRS, and the FBI.

登録情報

出版社 : Wiley; 第1版 (2013/11/12)
発売日 : 2013/11/12
言語 : 英語
ペーパーバック : 432ページ
ISBN-10 : 111866146X
ISBN-13 : 978-1118661468
寸法 : 18.54 x 2.03 x 23.11 cm

Amazon 売れ筋ランキング: - 10,871位洋書 (の売れ筋ランキングを見る洋書)
- - 5位Data Warehousing
- - 7位Business Operations Research
- - 15位Data Mining

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267個の評価

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星4つ		16%
星3つ		7%
星2つ		4%
星1つ		3%

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J. Norman

cool author, and written with humour. Unfortunately this does not make it any easier

2014年10月5日に英国でレビュー済み

Amazonで購入

I almost gave this a lower rating because it is a challenging read - I thought a couple of times of packing it in halfway through which never makes you feel good about a book.

Thankfully I didn't, because it is a difficult subject matter, but there aren't any problems with the writing or content.

I have had to over it quite a few times to "get it" and there are still things I don't fully understand, but at least I can replicate to get results. Some readers might be able to grasp it first time, but I think many won't unless they already know about things such as Clustering and Exponential Smoothing.
If you are looking for a basic intro to Data Analysis you should avoid this, but if you are looking to really get stuck in, then buy it. Be warned what you are letting yourself in for: just browsing it or reading once and putting on the bookshelf will be of no use whatsoever. I've spent at least 30 hours on it so far.

Overall the content and the ideas are brilliant, and the guy is really really funny - still doesn't make it any easier.

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Colm Ginty

Entertaining and accessible view over difficult subject matter

2019年5月10日に英国でレビュー済み

Amazonで購入

As a software developer I wanted to dip my toe into Data Science as it is clearly a key trend for tech and for wider society. This book promised to be an accessible introduction. If Excel is its tool of choice it couldn't be too advanced! However, while the author's writing style is wonderfully unpretentious and entertaining, and he makes the content as easy as I can imagine it being made, these are not toy techniques. This is proper data science that has genuine applicability in the real world. If you can get your head around the contents of this book you'll be well-placed to add real value in any organisation.

This is a very valuable book that is well worth the effort.

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D Edwards

A brilliant foundation with actionable explanations

2014年12月5日に英国でレビュー済み

Amazonで購入

I took delivery of this book 4 days ago. Since then I was posed a question by a client who wanted to look at 3 year forecast of marketing potential. I am comfortable with this however the data they had was not brilliant and there were a lot of unknowns and statistical anomalies which made this extremely difficult. This book really enabled me to get to grips with how best to tackle these sorts of questions in a clear and concise way and ensure you are keeping an eye out for outliers and noise. It has since spurred me on to order another couple of more in-depth books on statistics and this has since proved to be an excellent foundation book on which to build expert knowledge.

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j b taylor

Makes relatively complex concepts very simple

2014年5月29日に英国でレビュー済み

Amazonで購入

This book is an excellent practical application of commonly used advanced analytical techniques for data analysis in Excel. I was skeptical that this was possible before purchasing the book and partly bought out of curiosity of to what extent it could be pulled off, but I was pleasantly surprised.

Those with a strong background in statistics and SAS/SPSS/R will find it interesting and find it useful for the purposes of helping other understand what they are doing (i.e. it isn't magic) - but the target audience would be for those trying to gain business insight (probably in SME's) who are technically able, but who only know and / or have access to one tool for solving the problem - i.e. Excel. There are a lot of people in this situation, and this book could dramatically widen their horizons when considering issues such as optimisation or customer insight.

Ultimately the author himself ends the book by stating that Excel isn't really the right tool for the job, and introduces R as an open source alternative. The demographic at which this book is aimed would most likely would not have considered this a possible path before they picked up this book, but I believe by the end of it most will give it proper consideration as a means to best apply the methods detailed within the book.

As an aside, the author has a quirky and amusing style, which went down well at least with me, such that I read the first 4 chapters in one sitting...

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JJ McChesney

Brilliant.

2019年10月27日に英国でレビュー済み

Amazonで購入

A lot has been written about data science, most of it just waffle or too technical. This book is brilliant. Pitched at the right level, hands-on and gives you a tool set you can actually use. Can't recommend this book enough.

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