Handbook of Statistical Analysis and Data Mining Applications

"This is for the data scientists! How can we have a list of books without having a representative from the major class of books, which is the technical ones? There are a million of them, and a lot of them are great. They’re the bread and butter I grew up on. They’re not for general readers. Among them, this book is very comprehensive. It also has a relatively large dose of business side vantage, not just the number crunching part, so it is unique in that way. And it makes your biceps really big because it’s a huge, thick, heavy book. Yes, they could. It’s a technical book, but it starts from ground zero: What does it mean to learn from data? The computer program is automatically finding patterns and formulas and, in that sense, learning from the historical data or the labeled data—what do those patterns look like? Sometimes they’re just if-then business rules, and my book gets into a little of that detail as well. This book gets into it in a much more technical way, but it does from the get-go. If you’re already a computer programmer, you’d understand it. If you’re already relatively mathematically oriented but you know nothing about machine learning, you’d follow it. If you’re a newcomer and you have no inclination in terms of math or technology, it would be a challenge to understand. It is meant to start from ground zero, but it assumes quantitative aptitude. You’ve got to be able to tell the difference between the hype and the reality because the hype is very prevalent. If you’re a general reader, it’s about getting a good sense of what this technology is. My two books are meant to ramp people up on the specific way it works and what it’s capable of. So is Evil Robots, Killer Computers, and Other Myths. In terms of the hype you could also read an article I wrote in the Harvard Business Review last spring: “The AI Hype Cycle is Distracting Companies.” I break down where it’s over promising, why the definition of AI is such a problem and why it matters. I’ve also written a follow-up article—that’s still forthcoming—that really tries to break down the problems with the argument that we’re headed towards AGI. It’s a myth and I list five fallacies in people’s thinking that lead them to believe this is true. The computer is not going to come alive. When you look at what concretely it can do, it’s very cool—and it’s not nearly that scary."