Artificial Neural Network

Artificial Neural Network Modelling  eBooks & eLearning

Posted by roxul at July 23, 2016
Artificial Neural Network Modelling

Subana Shanmuganathan and Sandhya Samarasinghe, "Artificial Neural Network Modelling"
English | ISBN: 3319284932 | 2016 | 482 pages | PDF | 14 MB

"Artificial Neural Networks: Models and Applications" ed. by Joao Luis G. Rosa  eBooks & eLearning

Posted by exLib at Oct. 22, 2016
"Artificial Neural Networks: Models and Applications" ed. by Joao Luis G. Rosa

"Artificial Neural Networks: Models and Applications" ed. by Joao Luis G. Rosa
ITexLi | 2016 | ISBN: 9535127055 9789535127055 9535127047 9789535127048 | 409 pages | PDF | 88 MB

This is a current book on Artificial Neural Networks and Applications, bringing recent advances in the area to the reader interested in this always-evolving machine learning technique.
Artificial Neural Networks - ICANN 2010: 20th International Conference, Thessaloniki, Greece (Repost)

Artificial Neural Networks - ICANN 2010: 20th International Conference, Thessaloniki, Greece , September 15-18, 2010, Proceedings, Part I - Konstantinos Diamantaras - Wlodek Duch - Lazaros S. Iliadis
English | 2010 | 587 Pages | ISBN: 3642158188 | PDF | 15.58 MB

th This volume is part of the three-volume proceedings of the 20 International Conference on Arti?cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during September 15-18, 2010. ICANN is an annual meeting sponsored by the European Neural Network Society (ENNS) in cooperation with the International Neural Network So- ety (INNS) and the Japanese Neural Network Society (JNNS). This series of conferences has been held annually since 1991 in Europe, covering the ?eld of neurocomputing, learning systems and other related areas…

Artificial Neural Networks - ICANN 2010 (repost)  eBooks & eLearning

Posted by interes at Nov. 18, 2016
Artificial Neural Networks - ICANN 2010 (repost)

Artificial Neural Networks - ICANN 2010 by Konstantinos Diamantaras, Wlodek Duch, Lazaros S. Iliadis
English | 2010 | ISBN: 3642158218 | 543 pages | PDF | 11 MB

Neural Network Programming with Java (repost)  eBooks & eLearning

Posted by andr1078 at Aug. 14, 2016
Neural Network Programming with Java (repost)

Alan M.F. Souza, Fabio M. Soares "Neural Network Programming with Java"
Publisher: Packt Publishing | English | 2016 | ISBN: 178588090X | 244 pages | PDF/EPUB | 17.7 MB

Artificial Neural Networks in Biological and Environmental Analysis (Repost)  eBooks & eLearning

Posted by roxul at July 19, 2016
Artificial Neural Networks in Biological and Environmental Analysis (Repost)

Grady Hanrahan, "Artificial Neural Networks in Biological and Environmental Analysis"
English | 2011 | ISBN-10: 1439812586 | PDF | 214 pages | 2,5 MB

Neural Network Learning and Expert Systems (Repost)  eBooks & eLearning

Posted by step778 at June 7, 2016
Neural Network Learning and Expert Systems (Repost)

Stephen I. Gallant, "Neural Network Learning and Expert Systems"
1993 | pages: 364 | ISBN: 0262071452 | DJVU | 4,6 mb

Neural Network Design (2nd Edition)  eBooks & eLearning

Posted by enmoys at May 8, 2016
Neural Network Design (2nd Edition)

Neural Network Design (2nd Edition) By Martin T Hagan, Howard B. Demuth, Mark Hudson Beale, Orlando De Jesús
2014 | 1012 Pages | ISBN: 0971732116 | PDF | 11 MB

Make Your Own Neural Network  eBooks & eLearning

Posted by AlenMiler at April 12, 2016
Make Your Own Neural Network

Make Your Own Neural Network by Tariq Rashid
English | Mar. 31, 2016 | ISBN: 1530826608 | 222 Pages | AZW3/MOBI/EPUB (conv) | 20.6 MB

A gentle journey through the mathematics of neural networks, and making your own using the Python computer language.

Neural Network Design and the Complexity of Learning [Repost]  eBooks & eLearning

Posted by tanas.olesya at March 16, 2016
Neural Network Design and the Complexity of Learning [Repost]

Neural Network Design and the Complexity of Learning by Js Judd
English | 6 Jun. 1990 | ISBN: 0262100452 | 150 Pages | PDF | 10 MB

Using the tools of complexity theory, Stephen Judd develops a formal description of associative learning in connectionist networks. He rigorously exposes the computational difficulties in training neural networks and explores how certain design principles will or will not make the problems easier.