Learning From Data by Yaser S. Abu Mostafa

Utility-Based Learning from Data by Craig Friedman and Sven Sandow (Repost)  eBooks & eLearning

Posted by serpmolot at May 22, 2012
Utility-Based Learning from Data by Craig Friedman and Sven Sandow (Repost)
Utility-Based Learning from Data (Chapman & Hall/CRC Machine Learning & Pattern Recognition) by Craig Friedman and Sven Sandow (Repost)
English | 2010 | ISBN: 1584886226 | 412 pages | PDF | 3.25 MB

Statistics: The Art and Science of Learning from Data, Global Edition  eBooks & eLearning

Posted by AlenMiler at Jan. 20, 2017
Statistics: The Art and Science of Learning from Data, Global Edition

Statistics: The Art and Science of Learning from Data by Alan Agresti
English | 15 Mar. 2017 | ISBN: 1292164778, 1292164875 | 816 Pages | PDF (True) | 42.24 MB

Statistics: The Art and Science of Learning from Data, Fourth Edition, takes a conceptual approach, helping students understand what statistics is about and learning the right questions to ask when analyzing data, rather than just memorizing procedures.

Statistics: Learning from Data  eBooks & eLearning

Posted by ksveta6 at Oct. 4, 2015
Statistics: Learning from Data

Statistics: Learning from Data by Roxy Peck
2014 | ISBN: 0495553263 | English | 720 pages | PDF | 68 MB

Learning From Data  eBooks & eLearning

Posted by arundhati at March 20, 2015
Learning From Data

Yaser S. Abu-Mostafa, Malik Magdon-Ismail, "Learning From Data"
2012 | ISBN-10: 1600490069 | 213 pages | PDF | 26 MB

Utility-Based Learning from Data (repost)  eBooks & eLearning

Posted by interes at May 15, 2014
Utility-Based Learning from Data (repost)

Utility-Based Learning from Data by Craig Friedman and Sven Sandow
English | 2010 | ISBN: 1584886226 | 417 pages | PDF | 2,7 MB

Utility-Based Learning from Data provides a pedagogical, self-contained discussion of probability estimation methods via a coherent approach from the viewpoint of a decision maker who acts in an uncertain environment.
Advanced Analytics with Spark: Patterns for Learning from Data at Scale, 2nd Edition

Advanced Analytics with Spark: Patterns for Learning from Data at Scale, 2nd Edition by Sandy Ryza, Uri Laserson, Sean Owen, Josh Wills
English | July 6th, 2017 | ISBN: 1491972955, 9781491972953 | 275 pages | True PDF | 5.21 MB

In the second edition of this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. Updated for Spark 2.1, this edition acts as an introduction to these techniques and other best practices in Spark programming.

Statistics: The Art and Science of Learning from Data (3rd edition) [Repost]  eBooks & eLearning

Posted by ChrisRedfield at July 23, 2017
Statistics: The Art and Science of Learning from Data (3rd edition) [Repost]

Alan Agresti, Christine A. Franklin - Statistics: The Art and Science of Learning from Data (3rd edition)
Published: 2012-01-06 | ISBN: 0321755944, 0321756320 | PDF | 832 pages | 39.67 MB
Advanced Analytics with Spark: Patterns for Learning from Data at Scale, 2nd Edition

Advanced Analytics with Spark: Patterns for Learning from Data at Scale, 2nd Edition by Sandy Ryza, Uri Laserson, Sean Owen, Josh Wills
English | July 7, 2017 | ISBN: 1491972955 | EPUB | 280 pages | 4.7 MB

Advanced Analytics with Spark: Patterns for Learning from Data at Scale  eBooks & eLearning

Posted by AlenMiler at June 15, 2017
Advanced Analytics with Spark: Patterns for Learning from Data at Scale

Advanced Analytics with Spark: Patterns for Learning from Data at Scale by Sandy Ryza
English | 12 Jun. 2017 | ASIN: B072KFWZ8S | 281 Pages | AZW3 | 1.81 MB

Learning From Data - Introductory Machine Learning Course  eBooks & eLearning

Posted by FenixN at Nov. 28, 2016
Learning From Data - Introductory Machine Learning Course

Learning From Data - Introductory Machine Learning Course
HDRips | MP4/AVC, ~222 kb/s | 1280x720 | Duration: 23:36:03 | English: AAC, 96 kb/s (2 ch) | 3.22 GB
Genre: Science

This introductory computer science course in machine learning will cover basic theory, algorithms, and applications. Machine learning is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to automatically learn how to perform a desired task based on information extracted from the data. Machine learning has become one of the hottest fields of study today and the demand for jobs is only expected to increase. Gaining skills in this field will get you one step closer to becoming a data scientist or quantitative analyst.