Machine Learning The Art And Science Of Algorithms That Make Sense Of Data > shorl.com/tragestynokype
5d814c0f19 Description Product filter button Description Contents Resources Courses About the Authors As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. This book changed that for me. Thank you for your feedback which will help us improve our service. πRendered by PID 18469 on app-256 at 2016-07-03 17:14:18.099364+00:00 running aaa9f9d country code: NL. Rule models 7.
Written as a concise introduction to statistics for computer scientists. Prologue and Chapter 1 are freely available online Pedagogic features include boxes summarising relevant background material and a list of 'important points to remember' Epilogue includes open problems in machine learningRead moreReviews & endorsements"This textbook is clearly written and well organized. Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. You will be asked to input your password on the next screen. Pattern Recognition and Machine Learning, by Chris Bishop, 2007, Springer. This book is an introductory text on machine learning. More Mathematical/Statistical Texts Learning from Data, Abu-Mostafa, Magdon-Ismail, and Lin, 2012. He is Editor-in-Chief of Machine Learning and Program Co-Chair of the 2009 ACM Conference on Knowledge Discovery and Data Mining and the 2012 European Conference on Machine Learning and Data Mining. Cancel Not already registered? Create an account now. The material includes necessary mathematical detail, but emphasises intuitions and how-to.
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