Convolutional Neural Networks

Convolutional Neural Networks in Python  eBooks & eLearning

Posted by arundhati at July 7, 2016
Convolutional Neural Networks in Python

LazyProgrammer, "Convolutional Neural Networks in Python: Master Data Science and Machine Learning with Modern Deep Learning in Python, Theano, and TensorFlow"
2016 | ASIN: B01FQDREOK | 52 pages | EPUB | 1 MB

NEURAL NETWORKS  eBooks & eLearning

Posted by AlenMiler at Nov. 5, 2016
NEURAL NETWORKS

NEURAL NETWORKS by RAGHAVA SHANKAR
English | 1 Oct 2016 | ASIN: B01LY27DHK | 105 Pages | AZW3/MOBI/EPUB/PDF | 6.63 MB

What are neural networks in a nutshell? Neural networks is a technology book that deals with both natural and our artificial lifestyle.

NEURAL NETWORKS with MATLAB  eBooks & eLearning

Posted by AlenMiler at Oct. 29, 2016
NEURAL NETWORKS with MATLAB

NEURAL NETWORKS with MATLAB by Marvin L.
English | 23 Oct. 2016 | ISBN: 1539701956 | 418 Pages | PDF | 2.05 MB

Neural Network Toolbox provides algorithms, functions, and apps to create, train, visualize, and simulate neural networks.

Deep Learning: Recurrent Neural Networks in Python  eBooks & eLearning

Posted by AlenMiler at Sept. 10, 2016
Deep Learning: Recurrent Neural Networks in Python

Deep Learning: Recurrent Neural Networks in Python: LSTM, GRU, and more RNN machine learning architectures in Python and Theano (Machine Learning in Python) by LazyProgrammer
English | 8 Aug 2016 | ASIN: B01K31SQQA | 86 Pages | AZW3/MOBI/EPUB/PDF (conv) | 1.44 MB

Like Markov models, Recurrent Neural Networks are all about learning sequences - but whereas Markov Models are limited by the Markov assumption, Recurrent Neural Networks are not - and as a result, they are more expressive, and more powerful than anything we’ve seen on tasks that we haven’t made progress on in decades.
A Statistical Approach to Neural Networks for Pattern Recognition by Robert A. Dunn [Repost]

A Statistical Approach to Neural Networks for Pattern Recognition by Robert A. Dunne
English | July 16, 2007 | ISBN: 0471741086 | 288 Pages | PDF | 10 MB

An accessible and up-to-date treatment featuring the connection between neural networks and statistics. A Statistical Approach to Neural Networks for Pattern Recognition presents a statistical treatment of the Multilayer Perceptron (MLP), which is the most widely used of the neural network models.

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

Power Converters and AC Electrical Drives with Linear Neural Networks (Repost)  eBooks & eLearning

Posted by roxul at Nov. 10, 2016
Power Converters and AC Electrical Drives with Linear Neural Networks (Repost)

Maurizio Cirrincione, Marcello Pucci, "Power Converters and AC Electrical Drives with Linear Neural Networks"
English | 2012 | ISBN-10: 1439818142 | 661 pages | PDF | 24,4 MB
Data Mining with Neural Networks: Solving Business Problems from Application Development to Decision Support [Repost]

Joseph P. Bigus - Data Mining with Neural Networks: Solving Business Problems from Application Development to Decision Support
1996 | ISBN: 0070057796 | English | 220 pages | DJVU | 2.8 MB

Issues in the Use of Neural Networks in Information Retrieval  eBooks & eLearning

Posted by arundhati at Oct. 22, 2016
Issues in the Use of Neural Networks in Information Retrieval

Iuliana F. Iatan, "Issues in the Use of Neural Networks in Information Retrieval"
2016 | ISBN-10: 3319438700 | 199 pages | PDF | 7 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.