Machine Learning And Statistical

Udemy - Machine Learning and Statistical Modeling with R Examples

Udemy - Machine Learning and Statistical Modeling with R Examples
MP4 | Video: 1280x720 | 56 kbps | 48 KHz | Duration: 3 Hours | 531 MB
Genre: eLearning | Language: English

Learn how to use machine learning algorithms and statistical modeling for clustering, decision trees, etc by using R
Machine Learning and Statistical Modeling Approaches to Image Retrieval (repost)

Machine Learning and Statistical Modeling Approaches to Image Retrieval By Yixin Chen, Jia Li, James Z. Wang
Publisher: Sp..rin..ger 2004 | 199 Pages | ISBN: 1402080344 | PDF | 7 MB
Machine Learning and Data Science: An Introduction to Statistical Learning Methods with R

Machine Learning and Data Science: An Introduction to Statistical Learning Methods with R by Daniel D. Gutierrez
English | 18 Sept. 2015 | ISBN: 1634620968 | 282 Pages | True AZW3 (Kindle)/(EPUB/PDF conv) | 15.44 MB

A practitioner's tools have a direct impact on the success of his or her work. This book will provide the data scientist with the tools and techniques required to excel with statistical learning methods in the areas of data access, data munging, exploratory data analysis, supervised machine learning, unsupervised machine learning and model evaluation.
Machine Learning and Interpretation in Neuroimaging: 4th International Workshop, MLINI 2014, Held at NIPS 2014, Montreal, QC, C

Machine Learning and Interpretation in Neuroimaging: 4th International Workshop, MLINI 2014, Held at NIPS 2014, Montreal, QC, Canada, December 13, … Papers
Irina Rish, Georg Langs | 2016 | EPUB, PDF(conv) | ISBN: 3319451731 | 128 pages | 1 Mb, 4 Mb

Advances in Machine Learning and Signal Processing  eBooks & eLearning

Posted by AlenMiler at July 15, 2016
Advances in Machine Learning and Signal Processing

Advances in Machine Learning and Signal Processing: Proceedings of MALSIP 2015 (Lecture Notes in Electrical Engineering) by Ping Jack Soh
English | 7 July 2016 | ISBN: 3319322125 | 324 Pages | PDF (True) | 9.6 MB

This book presents important research findings and recent innovations in the field of machine learning and signal processing.

Machine Learning and Knowledge Discovery in Databases  eBooks & eLearning

Posted by leonardo78 at July 4, 2016
Machine Learning and Knowledge Discovery in Databases

Machine Learning and Knowledge Discovery in Databases: European Conference, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part II by Walter Daelemans, Katharina Morik
Publisher: Springer | 2008 | ISBN: 3540874801 | 698 pages | PDF | 24,7 MB

This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008.
Introducing Data Science: Big Data, Machine Learning, and more, using Python tools

Davy Cielen, Arno Meysman, Mohamed Ali, "Introducing Data Science: Big Data, Machine Learning, and more, using Python tools"
English | ISBN: 1633430030 | 2016 | PDF/EPUB | 320 pages | 15 MB/13 MB

Graphical Models for Machine Learning and Digital Communication  eBooks & eLearning

Posted by step778 at June 8, 2016
Graphical Models for Machine Learning and Digital Communication

Brendan J. Frey, "Graphical Models for Machine Learning and Digital Communication"
1998 | pages: 203 | ISBN: 026206202X | DJVU | 1,6 mb
Apache Hadoop - Machine Learning and Hadoop Eco System

Apache Hadoop - Machine Learning and Hadoop Eco System
MP4 | Video: 1280x720 | 53 kbps | 44 KHz | Duration: 2 Hours | 152 MB
Genre: eLearning | Language: English

Integrating Hadoop into the Enterprise Workflow, Machine Learning & Mahout, Hadoop Eco System Projects, HIVE, PIG, Oozie

Machine Learning and Knowledge Discovery in Databases  

Posted by tanas.olesya at Dec. 20, 2015
Machine Learning and Knowledge Discovery in Databases

Machine Learning and Knowledge Discovery in Databases by Hendrik Blockeel
English | 26 Aug. 2013 | ISBN: 3642409903 | 732 Pages | PDF | 13 MB

The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis;