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 developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package―PMTK (probabilistic modeling toolkit)―that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

About the Author

Kevin P. Murphy is a Research Scientist at Google. Previously, he was Associate Professor of Computer Science and Statistics at the University of British Columbia.

"About this title" may belong to another edition of this title.

Store Description

We sell Brand New University Textbooks to students at very affordable prices. All orders are shipped by Trackable methods only and the tracking number is available within 48 hours of placing the order. We also offer free shipping to USA, Canada and Europe and lowest shipping charges in other countries. We have multiple warehouses to save on the transit time.

Visit Seller's Storefront

Seller's business information

SMASS Group LLC
1944 Loma Linda Dr, Irving, TX, 75063, U.S.A.

Sale & Shipping Terms

Terms of Sale

We sell Brand New Textbooks requied for studies in the Univesity. We have been in this business for the past 14 years and we know how to keep our customers happy and satisfies by providing them the required course material and the most affordable prices.

Shipping Terms

We ship all orders from our Multiple warehouses by Tracakble method only. We have tie up with Fedex, DHL, UPS and USPS for our logistics requirements. All tracking numbers are available within 48 hours of processing the order.