“Through this wonderful book, frustrated golfers can learn to swing like Moe [Norman] and improve their games.” —Anthony Robbins, #1 New York Times–bestselling author The mysterious and reclusive genius Moe Norman is acknowledged as the best ball-striker in the history of golf by many of the game’s greats. The Single Plane Golf Swing: Play Better Golf the Moe Norman Way reveals the secrets of the swing that enabled him to hit the ball solidly with unerring accuracy and consistency—every time. Norman’s simple, efficient, and easily understood Single Plane Swing has improved the games of thousands of golfers. Golf professional Todd Graves, known as “Little Moe” and regarded as the world authority on Norman’s swing, comprehensively teaches readers the mechanics, drills, and feelings of the Single Plane Swing that Moe called “The Feeling of Greatness.” Graves shares Norman’s brilliant insights and liberating approach to the game and demonstrates why the conventional “tour” swing is too complex and frustrating for the majority of amateurs. Illustrated with more than 300 photographs and written with Tim O’Connor, Norman’s biographer, the book also engagingly tells Norman’s bittersweet life story and explores the teacher-student bond forged between Norman and his protégé Graves. “One of golf’s greatest untold stories, Moe Norman’s life illustrated a simple and powerful truth: greatness is built from practicing the right swing in the right way. In this book, Todd Graves has given us a blueprint for that swing, for those practice habits, and most of all for a process that builds success.” —Dan Coyle, New York Times-bestselling author of The Culture Code

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.