Bayesian Reasoning and Machine Learning Tapa dura - 2012

Cambridge University Press. 1. Very Good. Very Good. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported

CAMBRIDGE. Softcover. Brand New. “International Edition” - ISBN number and front cover may be different in rare cases but CONTENTS are same as the US edition. No shipping to PO BOX, APO, FPO addresses. Kindly provide day time phone number in order to ensure smooth delivery. Printed in black & white in English language. Territorial restrictions may be printed on the book. We may ship from Asian regions for inventory purpose. 100% Customer satisfaction guaranteed!" We use Fast Shipping via DHL/FEDEX/UPS

Good. Exact ISBN match. Immediate shipping. No funny business. Pics available upon request.

2012-03-12T00:00:01Z. New. 2012-03-12T00:00:01Z New All orders ship SAME or NEXT business day Expedited shipments will be received in 5-12 business days within the United States 100% Satisfaction Guaranteed!

Hardback. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; This practical introduction for final-year undergraduate and graduate students is ideally suited to computer scientists without a background in calculus and linear algebra. Numerous examples and exercises are provided. Additional resour

Cambridge University Press, 2012-03-12. Hardcover. Good. US Edition Textbook, May Have Highlights, Notes and/or Underlining, BOOK ONLY-NO ACCESS CODE, NO CD, Ships with Emailed Tracking from USA

Cambridge University Press, 2012. Hardcover. New. 650 pages. 9.76x7.48x1.50 inches.

Cambridge University Press, 2012. Hardcover. New. 650 pages. 9.76x7.48x1.50 inches.

Cambridge University Press CUP , pp. 720 Index. Hardback. New.

ISBN: 9780521518147
CAMBRIDGE UNIVERSITY PRESS | 15 February 2019
Hardback | 735 pages 
Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and… Leer más