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1. Finally. The best `water cooler talk’ book thus far about Data Mining
   I am a Data Miner and a Data Mining software trainer. I really enjoyed this book. My audience is not made of full time data miners (usually), but rather data analysts who are new to data mining. They are not experts who develop their own technologies, but rather are purchasers of software who use the software to Mine data with the most established of the techniques. They report to managers, and have co-workers, that are also new to data mining, curious about what it is, anxious to clarify its definition, wondering about possible application areas, working to effect the bottom line.I disagree with those reviewers that suggest that Baker does not understand the methods. He tries very hard at explaining them to a general audience. I have tried to do the same, and he does an admirable job. I would be less than candid, if I didn’t admit that I winced once or twice. But it is tough to strike the right balance.I think he has does a brilliant job at choosing a structure of his book. His chapters are not structured to be on the different methods. One negative review claims that he `mentions’ Support Vector Machines, but never mentions cluster analysis. It is simply not true. The “Voters” chapter is dedicated almost in its entirely to cluster analysis and market segmentation. I have taught this topic to thousands of software users, and I think it is a great chapter. He avoids technical jargon including the names of the methods because he audience is not me. His audience is everyone who does not do data mining, but is potentially effected by it, curious about it. So, if you want a chapter on how Support Vector Machines work, one can barely imagine a less appropriate choice. If you want a gentle introduction to many techniques like Neural Nets and Classification Trees go with Berry and Linoff’s Data Mining Techniques. 

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2. An interesting journey in the data mining world
   Whether you are a shopper, a voter or a blogger, you will find a chapter in The Numerati that will be of interest to you. Stephen Baker has done an excellent job in explaining what companies can do with their data. For getting knowledge from these data, companies use mathematicians and computer scientists (what Baker calls the numerati).Baker takes us in a journey divided in seven parts (chapters). Each of this parts explain the possible application of data mining in a specific area. The journey is passionate and thus very interesting to read. The main point of his book is the ability of companies to build our behavior by mining personal data in various domains. As he explains, this would be impractical manually:”This means that marketers must scope us out as individuals. One approach would be to deploy battalions of psychology […] That’s impractical.”The main question for companies that collect data about us is what do we do, that might predict what we will do next? The book gives answers with practical examples.By the way, Baker makes a very good vulgarization of decision trees on page 88. The author also makes a good point about data mining by stating that the aim is not to be perfect, but to do better:”Truth is not a make-or-brake test for the Numerati. They triumph if they come up with better, quicker or cheaper answers than the status quo.”To conclude, this is a very good book that any data miner should read to get a tour of possible applications. Maybe Baker goes a bit too far on what data mining can do (spy you) and this may frighten people:”In the age we’re entering, our lives will be described, studied, and predicted, every day more, through this statistical analysis.”

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3. The geek shall inherited the earth
   A couple years ago, a friend’s advice that I “skip the physics theory parts” enabled me to thoroughly enjoy Walter Isaacson’s biography of Albert Einstein. So I was prepared to jump over the “math part” of Steven Baker’s Numerati but was happy to discover that even the math-averse can enjoy this contemporary look at some of the country’s geekiest numbers jocks and the work they are doing. Rather, the book is a tight narrative exploring the personalities behind some of the most ambitious number-crunching projects imaginable: data mining to discover ways to solve healthcare challenges, find terrorists or soul mates, or unlock the mysteries of the marketplace by analyzing the words used by bloggers. Really.Baker’s story-telling skill brings life to the zeroes and ones of these data masters. And marketers — especially the metric-obsessed kind — will find the book a great over-view of current thinking on the potential of what measuring the data related to our daily lives and actions can reveal.Baker also points out the downside that occurs when people trade their privacy for convenience and customization. He echoes the concerns of privacy and civil liberty advocates (and science fiction authors) who warn us of the dark consequences of a society where all our actions are tracked and analyzed.After reading how these elite numbers superstars are creating a world in which search engines will appear to know what we’re seeking before we even know it, my only question is this: If these guys are so smart, how come the ATM I’ve been using for the past ten years hasn’t figured out yet that I rather do the transaction in English rather than Spanish.

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4. Great thank you

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5. Companies, political parties, advertisers and individuals are harnessing the masses of data in our increasingly digitised world to know more about us than ever before. Businesses like Amazon and Google sift through our every click (and solicit our feedback) to find out more about us so they can customise what they sell us, both to keep us happy as customers and to increase their profits. Supermarkets use loyalty schemes to pinpoint their sales promotions to good prospects in increasingly elaborate ways. Political parties know who the floating voters are and what messages will make them vote for their policies. How do they do it, and what are the implications for our privacy? There are few technical details here, but this is a good introduction to the world of data mining.

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6. This is well written journalism that concentrates on the numerati themselves. Nothing wrong with journalism per se (I was a journalist myself for some years), but there’s a bigger story to be written about than this. I was hoping for a more insightful analysis of the techniques, implications and/or limitations of mathematical and statistical analysis being applied at massive scale on the world around us. But what the author delivered was a set of interesting anecdotes.

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7. Great price.

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8. A simple, clear and interesting popular introduction to the now ubiquitous field of smart data analysis, making up also a label for people working this field: “numerati”

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