Fundamentals Of Machine Learning

Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies

Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies By John D. Kelleher
2015 | 624 Pages | ISBN: 0262029448 | EPUB | 7 MB
Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies

Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies by John D. Kelleher
English | July 24, 2015 | ISBN: 0262029448 | 624 Pages | AZW3/PDF (conv) | 24 MB

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification.

Fundamentals of Machine Theory and Mechanisms  eBooks & eLearning

Posted by Underaglassmoon at June 12, 2016
Fundamentals of Machine Theory and Mechanisms

Fundamentals of Machine Theory and Mechanisms
Springer | Mechanical Engineering Textbook | June 20 2016 | ISBN-10: 331931968X | 409 pages | pdf | 15.61 mb

Authors: Simón Mata, A., Bataller Torras, A., Cabrera Carrillo, J.A., Ezquerro Juanco, F., Guerra Fernández, A.J., Nadal Martínez, F., Ortiz Fernández, A.
Text written by experts with many years of experience
Every chapter includes application examples and exercises
Synthesis of mechanisms based on genetic algorithms
Fundamentals of Machine Component Design (5th edition) (Repost)

Fundamentals of Machine Component Design (5th edition) By Robert C. Juvinall, Kurt M. Marshek
2011 | 929 Pages | ISBN: 1118012895 | PDF | 29 MB
Fundamentals of Machine Elements, Third Edition: SI Version

Fundamentals of Machine Elements, Third Edition: SI Version by Steven R. Schmid and Bernard J. Hamrock
English | 2014 | ISBN: 1482247488, 143989132X | 625 pages | PDF | 112 MB
Rudy Kouhoupt - Fundamentals of Machine Lathe Operation [Repost]

Rudy Kouhoupt - Fundamentals of Machine Lathe Operation
DVD5 | VIDEO_TS, NTSC, 6083 kbps, 720x480 | English, AC3, 384 kbps, 2 Ch | 95 mins | 4.38 GB
Subject: Hobby/DIY
Electrical Machines: Mathematical Fundamentals of Machine Topologies (Repost)

Electrical Machines: Mathematical Fundamentals of Machine Topologies - Dieter Gerling
English | 2014 | 479 Pages | ISBN: 364217583X | PDF | 7.13 MB

Electrical Machines and Drives play a vital role in industry with an ever increasing importance. This fact necessitates the understanding of machine and drive principles by engineers of many different disciplines. Therefore, this book is intended to give a comprehensive deduction of these principles. Special attention is given to the precise mathematical deduction of the necessary formulae to calculate machines and drives, and to the discussion of simplifications (if applied) with the associated limits. So the book shows how the different machine topologies can be deduced from general fundamentals, and how they are linked…

Encyclopedia of Machine Learning (Repost)  

Posted by manamba13 at Feb. 28, 2015
Encyclopedia of Machine Learning (Repost)

Encyclopedia of Machine Learning by Claude Sammut
English | 2011 | ISBN: 0387307680 | 1059 Pages | PDF | 39 MB

This comprehensive encyclopedia, with over 250 entries in an A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of machine learning.
Electrical Machines: Mathematical Fundamentals of Machine Topologies

Dieter Gerling, "Electrical Machines: Mathematical Fundamentals of Machine Topologies"
English | ISBN: 364217583X | 2015 | 488 pages | PDF | 7 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.