Active Learning Techniques For Librarians. Practical Examples

3D Printing: A Practical Guide for Librarians (Practical Guides for Librarians)  eBooks & eLearning

Posted by AlenMiler at March 24, 2016
3D Printing: A Practical Guide for Librarians (Practical Guides for Librarians)

3D Printing: A Practical Guide for Librarians (Practical Guides for Librarians) by Sara Russell Gonzalez
English | Mar 30, 2016 | ISBN: 144225548X, 1442255471 | 190 Pages | AZW3/MOBI/EPUB/PDF (conv) | 18.18 MB

Planning and implementing a 3D printing service in a library may seem like a daunting task. Based upon the authors’ experience as early adopters of 3D technology and running a successful 3D printing service at a large academic library, this guide provides the steps to follow when launching a service in any type of library.

Practical Evaluation Techniques for Librarians  

Posted by tukotikko at July 17, 2015
Practical Evaluation Techniques for Librarians

Practical Evaluation Techniques for Librarians By Rachel Applegate
2013 | 244 Pages | ISBN: 1610691598 | PDF | 2 MB

Accelerated Learning Techniques for Students  eBooks & eLearning

Posted by moneyguzzler at June 4, 2016
Accelerated Learning Techniques for Students

Accelerated Learning Techniques for Students: Learn More in Less Time! by Joe McCullough
English | 2014 | ISBN-10: 1497344026 | 208 pages | ePUB | 1.1 MB
Accelerated Learning Techniques For Beginners: Effective Tips to Improve Your Memory and Reading Comprehension...

Accelerated Learning Techniques For Beginners: Effective Tips to Improve Your Memory and Reading Comprehension, Learn More and Faster, Enhance Intellect by Dale Blake
English | 2014 | ISBN: 1681270005 | 32 pages | EPUB | 0,1 MB

Machine Learning Techniques for Gait Biometric Recognition  

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

Learning: 25 Learning Techniques for Accelerated Learning - Learn Faster by 300%!  eBooks & eLearning

Posted by ksenya.b at Dec. 22, 2015
Learning: 25 Learning Techniques for Accelerated Learning - Learn Faster by 300%!

"Learning: 25 Learning Techniques for Accelerated Learning - Learn Faster by 300%!" by Sebastian Archer
2015 | EPUB | 108 pages | ISBN: 1514175541 | English | 0.1 MB
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
50 Games for Going Green: 50 Physically Active Learning Experiences for Children

Carol Scaini, Carolyn Evans, "50 Games for Going Green: 50 Physically Active Learning Experiences for Children"
English | ISBN: 1450419909 | 2012 | 120 pages | PDF | 17 MB
Realtime Data Mining: Self-Learning Techniques for Recommendation Engines (repost)

Alexander Paprotny, Michael Thess, "Realtime Data Mining: Self-Learning Techniques for Recommendation Engines: Toward the Self-Learning Recommendation Engine"
English | ISBN: 3319013203 | 2013 | 297 pages | PDF | 4 MB

Describing novel mathematical concepts for recommendation engines, Realtime Data Mining: Self-Learning Techniques for Recommendation Engines features a sound mathematical framework unifying approaches based on control and learning theories, tensor factorization, and hierarchical methods. Furthermore, it presents promising results of numerous experiments on real-world data.​ The area of realtime data mining is currently developing at an exceptionally dynamic pace, and realtime data mining systems are the counterpart of today's “classic” data mining systems. Whereas the latter learn from historical data and then use it to deduce necessary actions, realtime analytics systems learn and act continuously and autonomously. In the vanguard of these new analytics systems are recommendation engines. They are principally found on the Internet, where all information is available in realtime and an immediate feedback is guaranteed.
Realtime Data Mining: Self-Learning Techniques for Recommendation Engines: Toward the Self-Learning Recommendation Engine

Alexander Paprotny, Michael Thess, "Realtime Data Mining: Self-Learning Techniques for Recommendation Engines: Toward the Self-Learning Recommendation Engine"
English | ISBN: 3319013203 | 2013 | 297 pages | PDF | 4 MB