We live in a time of rapid change and what can feel like relentless uncertainty. Against this backdrop, the future often feels uncertain, leaving us searching for a path forward. This book offers strategies for navigating these times, beginning with ourselves and extending outward. Shaped in collaboration with one of the most cited scientists of our time, rooted in robust science (specifically active inference and free energy), and told through approachable stories, it pro...

LAMBDA LITERARY AWARD FINALIST'Essential reading' - THE INDEPENDENT'Vital and insightful' - OWL FISHERWhat does it mean to be non-binary in the 21st Century?Our gender identity is impacted by our personal histories; the cultures, communities and countries we are born into; and the places we go and the people we meet. But the representation of contemporary non-binary identities has been limit...

If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classificat...

Stress Test, one woman’s account of medical training in the 1970s, is particularly timely after the Dobbs decision. The story encompasses a five-year crucible, from the first day of medical school through the last day of pediatric internship. Unveiling the cadaver in the anatomy lab while her mother lay dying on an oncology ward; the excitement of making difficult diagnoses and the terror and tragedy of disastrous mistakes; the joy of connecting with patients and the heartbreak of losing t...

If you’re an experienced programmer willing to crunch data, this concise guide will show you how to use machine learning to work with email. You’ll learn how to write algorithms that automatically sort and redirect email based on statistical patterns. Authors Drew Conway and John Myles White approach the process in a practical fashion, using a case-study driven approach rather than a traditional math-heavy presentation.This book also includes a short tutorial on using the popular R...

'Excellent' KATE BORNSTEIN'The compassionate, accessible manual the world has been waiting for' LAURIE PENNYHave you ever questioned your own gender identity? Do you know somebody who is transgender or who identifies as non-binary? Do you ever feel confused when people talk about gender diversity?This down-to-earth guide is for anybody who wants to know more about gender, from its biology, history and sociology, to how it plays a rol...

Are you wrestling with questions surrounding your gender that just don’t seem to go away? Do you want answers to questions about your gender identity, but aren’t sure how to get started?In this groundbreaking guide, Dara Hoffman-Fox, LPC—accomplished gender therapist and thought leader whose articles, blogs, and videos have empowered thousands worldwide—helps you navigate your journey of self-discovery in three approachable stages: preparation, reflection, and exploration.I...

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain...

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics ...

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 n...

Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found ...

Building a simple but powerful recommendation system is much easier than you think. Approachable for all levels of expertise, this report explains innovations that make machine learning practical for business production settings—and demonstrates how even a small-scale development team can design an effective large-scale recommendation system.Apache Mahout committers Ted Dunning and Ellen Friedman walk you through a design that relies on careful simplification. You’ll learn how to c...