Posted by **leonardo78** at Aug. 2, 2017

Language: English | 2007 | ISBN: 0387310738 | 738 pages | PDF | 4,51 MB

This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible.

Posted by **ParRus** at Nov. 5, 2016

WEBRip | English | MP4 + PDF Guide | 640 x 360 | AVC ~250 kbps | 30 fps

AAC | 123 Kbps | 44.1 KHz | 2 channels | ~24 hours | 4.42 GB

Online Introduction to Artificial Intelligence is based on Stanford CS221, Introduction to Artificial Intelligence. This class introduces students to the basics of Artificial Intelligence, which includes machine learning, probabilistic reasoning, robotics, and natural language processing. The objective of this class is to teach you modern AI. You learn about the basic techniques and tricks of the trade, at the same level we teach our Stanford students. We also aspire to excite you about the field of AI. Whether you are a seasoned professional, a college student, or a curious high school student - everyone can participate.

Posted by **Underaglassmoon** at July 14, 2016

Springer | Mathematics | July 30 2016 | ISBN-10: 3319332538 | 390 pages | pdf | 3.45 mb

Authors: Zaslavski, Alexander J.

Examines the convergence of component-averaged row projections [CARP]

Extends results for a dynamic string-averaging version of the proximal algorithm

Posted by **Grev27** at May 14, 2016

English | ISBN: 1784392057 | 2016 | PDF/EPUB/MOBI | 250 pages | 4 MB/7 MB/11 MB

Posted by **libr** at Jan. 28, 2016

English | 2014 | ISBN: 1482215861 | 320 pages | PDF | 11 MB

Posted by **AlenMiler** at Aug. 13, 2015

English | 26 July 2015 | ISBN: 1784394688 | 284 Pages | EPUB/MOBI/PDF (True) | 34.35 MB

If you are a researcher or a machine learning enthusiast, or are working in the data science field and have a basic idea of Bayesian learning or probabilistic graphical models, this book will help you to understand the details of graphical models and use them in your data science problems.

Posted by **interes** at June 30, 2015

English | 2014 | ISBN: 1482215861 | 320 pages | PDF | 11 MB

Posted by **interes** at April 28, 2015

English | 2014 | ISBN: 1482215861 | 320 pages | PDF | 11 MB

Posted by **exLib** at Sept. 2, 2014

RoJo, BoBoCoAe | 2014 | ISBN: 8740307522 9788740307528 | 198 pages | PDF | 10 MB

This volume is dedicated to statistical inference - a process of drawing general conclusions from data in a specific sample. The present book differs from the latter since it focuses on problem solving and only a minimum of the theory needed is presented.

Posted by **exLib** at April 29, 2014

InTAvE | 2014 | ISBN: 953511364X 9789535113645 | 160 pages | PDF | 10 MB

The purpose of this book is to provide some applications of Bayesian optimization and dynamic programming.