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Probabilistic Machine Learning
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...
Machine Learning
A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach. Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developm...
Nelson Textbook of Pediatrics E-Book
Welcome to the 21st Edition of Nelson Textbook of Pediatrics – the reference of choice among pediatricians, pediatric residents, and others involved in the care of young patients. This fully revised edition continues to provide the breadth and depth of knowledge you expect from Nelson, while also keeping you up to date with new advances in the science and art of pediatric practice. Authoritative and reader-friendly, it delivers the information you need in a concise, easy-to-use format for everyday reference and study. From rapidly changing diagnostic and treatment protocols to new technologies to the wide range of biologic, psychologic, and social problems faced by children today, this com...
Nelson Textbook of Pediatrics E-Book
After more than 75 years, Nelson Textbook of Pediatrics remains your indispensable source for definitive, state-of-the-art answers on every aspect of pediatric care. Embracing the new advances in science as well as the time-honored art of pediatric practice, this classic reference provides the essential information that practitioners and other care providers involved in pediatric health care throughout the world need to understand to effectively address the enormous range of biologic, psychologic, and social problems that our children and youth may face. Brand-new chapters and comprehensive revisions throughout ensure that you have the most recent information on diagnosis and treatment of pe...
Probabilistic Machine Learning
An advanced book for researchers and graduate students working in machine learning and statistics who want to learn about deep learning, Bayesian inference, generative models, and decision making under uncertainty. An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics in machine learning, including deep generative modeling, graphical models, Bayesian inference, reinforcement learning, and causality. This volume puts deep learning into a larger statistical context and unifies approaches based on deep learning with ones based on probabilistic modeling and inference...
The Writer
The oldest magazine for literary workers.
Federal Yellow Book
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