Work the System
by Sam Carpenter
Alice’s Adventures in Wonderland Lewis Carroll
by Lewis Carroll
Великий Гэтсби. Книга для чтения на английском языке
by Френсис Фицджеральд
by Melissa Hartwig, Dallas Hartwig
Millions of people visit Whole30.com every month and share their dramatic life-changing testimonials. Get started on your Whole30 transformation with the #1 New York Times best-selling The Whole30.
Since 2009, Melissa Hartwig’s critically-acclaimed Whole30 program has quietly led hundreds of thousands of people to effortless weight loss and better health–along with stunning improvements in sleep quality, energy levels, mood, and self-esteem. The program accomplishes all of this by specifically targeting people’s habits and emotional relationships with food. The Whole30 is designed to help break unhealthy patterns of behavior, stop stress-related comfort eating, and reduce cravings, particularly for sugar and carbohydrates. Many Whole30 participants have described achieving “food freedom”–in just thirty days.
Now, The Whole30 offers a stand-alone, step-by-step plan to break unhealthy habits, reduce cravings, improve digestion, and strengthen your immune system. The Whole30 prepares participants for the program in five easy steps, previews a typical thirty days, teaches the basic meal preparation and cooking skills needed to succeed, and provides a month’s worth of recipes designed to build confidence in the kitchen and inspire the taste buds. Motivating and inspiring with just the right amount of signature tough love, The Whole30 features real-life success stories, an extensive quick-reference FAQ, detailed elimination and reintroduction guidelines, and more than 100 recipes using familiar ingredients, from simple one-pot meals to complete dinner party menus.
An Introduction to Statistical Learning
by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.
Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.