Today's Web-enabled deluge of electronic data calls for automated methods of dataanalysis. Machine learning provides these, developing methods that can automatically detect patternsin data and then us
In a 1907 lecture to Harvard undergraduates, Theodore Roosevelt warned against becoming "too fastidious, too sensitive to take part in the rough hurly-burly of the actual work of the world." Roosevelt
In a 1907 lecture to Harvard undergraduates, Theodore Roosevelt warned against becoming "too fastidious, too sensitive to take part in the rough hurly-burly of the actual work of the world."
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the ne
In this special issue of Radical History Review, scholars and activists examine the rise of “homonormativity,” a lesbian and gay politics that embraces neoliberal values under the guise o
The Twin Cities is home to one of the largest and most vital GLBT populations in the nation-and one of the highest percentages of gay residents in the country. Drawn from the pioneering work of the T
The second and expanded edition of a comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.This textbook offers a comprehensive and self-co
