R Unleash Machine Learning Techniques

R: Unleash Machine Learning Techniques  eBooks & eLearning

Posted by Grev27 at Oct. 27, 2016
R: Unleash Machine Learning Techniques

Raghav Bali, Dipanjan Sarkar, Brett Lantz, Cory Lesmeister, "R: Unleash Machine Learning Techniques"
English | ISBN-13: 9781787127340, ASIN: B01MQ4M4VO | 2016 | PDF/EPUB/MOBI | 1123 pages | 26 MB/32 MB/49 MB

Practical Guide to Cluster Analysis in R: Unsupervised Machine Learning  eBooks & eLearning

Posted by andr1078 at May 17, 2017
Practical Guide to Cluster Analysis in R: Unsupervised Machine Learning

Mr. Alboukadel Kassambara "Practical Guide to Cluster Analysis in R: Unsupervised Machine Learning "
Publisher: CreateSpace Independent Publishing Platform | English | 2017 | ISBN: 1542462703 | 188 pages | PDF | 5 MB

This book provides practical guide to cluster analysis, elegant visualization and interpretation.

PREDICTIVE ANALYTICS with MATLAB. MACHINE LEARNING TECHNIQUES  eBooks & eLearning

Posted by naag at May 3, 2017
PREDICTIVE ANALYTICS with MATLAB. MACHINE LEARNING TECHNIQUES

PREDICTIVE ANALYTICS with MATLAB. MACHINE LEARNING TECHNIQUES
2017 | English | ISBN-10: 1546422749 | 440 pages | PDF + EPUB (conv) | 16.5 Mb

R: Complete Machine Learning and Deep Learning Solutions  eBooks & eLearning

Posted by naag at April 15, 2017
R: Complete Machine Learning and Deep Learning Solutions

R: Complete Machine Learning and Deep Learning Solutions
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 16 Hours | 4.33 GB
Genre: eLearning | Language: English
Learning Deep Architectures for AI (Foundations and Trends(r) in Machine Learning)

Learning Deep Architectures for AI (Foundations and Trends(r) in Machine Learning) by Yoshua Bengio
English | Oct. 28, 2009 | ISBN: 1601982941 | 130 Pages | PDF | 1 MB

Can machine learning deliver AI? Theoretical results, inspiration from the brain and cognition, as well as machine learning experiments suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one would need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers, graphical models with many levels of latent variables, or in complicated propositional formulae re-using many sub-formulae.
Modern Machine Learning Techniques and Their Applications in Cartoon Animation Research (repost)

Modern Machine Learning Techniques and Their Applications in Cartoon Animation Research
by Jun Yu, Dacheng Tao
English | 2013 | ISBN: 1118115147 | 208 pages | PDF | 7.37 MB

Machine Learning Techniques for Gait Biometric Recognition  eBooks & eLearning

Posted by Underaglassmoon at Feb. 11, 2016
Machine Learning Techniques for Gait Biometric Recognition

Machine Learning Techniques for Gait Biometric Recognition: Using the Ground Reaction Force
Springer | Signals & Communication | March 7, 2016 | ISBN-10: 331929086X | 223 pages | pdf | 5.18 mb

Authors: Mason, James Eric, Traoré, Issa, Woungang, Isaac
Introduces novel machine-learning-based temporal normalization techniques
Bridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognition
Provides detailed discussions of key research challenges and open research issues in gait biometrics recognition
Compares biometrics systems trained and tested with the same footwear against those trained and tested with different footwear
Machine Learning Techniques for Multimedia: Case Studies on Organization and Retrieval

Matthieu Cord, Padraig Cunningham, "Machine Learning Techniques for Multimedia: Case Studies on Organization and Retrieval"
2008 | pages: 307 | ISBN: 354075170X | PDF | 23,8 mb
Modern Machine Learning Techniques and Their Applications in Cartoon Animation Research (Repost)

Modern Machine Learning Techniques and Their Applications in Cartoon Animation Research By Jun Yu, Dacheng Tao
2013 | 208 Pages | ISBN: 1118115147 | PDF | 8 MB
Analysis and Design of Machine Learning Techniques: Evolutionary Solutions for Regression, Prediction, and Control Problems

Analysis and Design of Machine Learning Techniques: Evolutionary Solutions for Regression, Prediction, and Control Problems by Patrick Stalph
English | 2014 | ISBN: 3658049367 | 155 pages | PDF | 3 MB

Manipulating or grasping objects seems like a trivial task for humans, as these are motor skills of everyday life. Nevertheless, motor skills are not easy to learn for humans and this is also an active research topic in robotics. However, most solutions are optimized for industrial applications and, thus, few are plausible explanations for human learning.