募捐 9月15日2024 – 10月1日2024 关于筹款

Backpropagation: Theory, Architectures, and Applications

Main
Society, Politics & Philosophy - Social Sciences
Backpropagation: Theory, Architectures,...

Backpropagation: Theory, Architectures, and Applications

Yves Chauvin (ed.), David E. Rumelhart (ed.)

0 / 0

你有多喜欢这本书？

下载文件的质量如何？

下载该书，以评价其质量

下载文件的质量如何？

种类:

Society, Politics & Philosophy - Social Sciences

年:

1995

出版社:

Lawrence Erlbaum Associates

语言:

english

页:

575

ISBN 10:

0805812598

ISBN 13:

9780805812596

系列:

Developments in Connectionist Theory

文件:

PDF, 13.87 MB

IPFS:

,

english, 1995

线上阅读

正在转换

转换为失败

您可能会感兴趣

James L. McClelland, Robert S. Siegler — Mechanisms of cognitive development: behavioral and neural perspectives

McClelland J.L., Rumelhart D.E. — Parallel Distributed Processing. Explorations in the Microstructure of Cognition. Volume 2. Psychological and Biological Models

Maynard, Morgan — Neural Networks: Introduction to Artificial Neurons, Backpropagation and Multilayer Feedforward Neural Networks with Real-World Applications (Advanced Data Analytics Book 2)

Benjamin Martin Bly, David E. Rumelhart — Cognitive Science

Suzanne Nalbantian, Paul M. Matthews, James L. McClelland (eds.) — The Memory Process: Neuroscientific and Humanistic Perspectives

David E. Rumelhart, James L. McClelland, PDP Research Group — Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 1 : Foundations

James L. McClelland, Jerome Feldman, Patrick Hayes, David E. Rumelhart — Parallel Distributed Processing, Vol. 2: Psychological and Biological Models

Marvin Minsky, Seymour A. Papert — Perceptrons: An Introduction to Computational Geometry

James L. McClelland, David E. Rumelhart — Explorations in Parallel Distributed Processing - Macintosh version: A Handbook of Models, Programs, and Exercises

David E. Rumelhart, James L. McClelland, PDP Research Group — Parallel Distributed Processing, Vol. 1: Foundations

Nikolaev N., Iba H. — Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods

Martin Anthony, Peter L. Bartlett — Neural Network Learning: Theoretical Foundations

Pat Nakamoto — Neural Networks and Deep Learning: Deep Learning Explained to Your Granny - a Visual Introduction for Beginners Who Want to Make Their Own Deep Learning Neural Network

MIT Press — Neural Computation, Volume 01 (1989) issue 1, 2, 3, 4

Ian Goodfellow, Yoshua Bengio, Aaron Courville — Deep Learning

Ian Goodfellow Yoshua Bengio Aaron Courville — Deep Learning

Ian Goodfellow, Yoshua Bengio, Aaron Courville — Deep learning

Ian Goodfellow; Yoshua Bengio; Aaron Courville — Deep Learning

Krose B. — An introduction to neural networks

Ian Goodfellow, Yoshua Bengio, Aaron Courville — Deep Learning

Ian Goodfellow, Yoshua Bengio, Aaron Courville — Deep Learning [pre-pub version]

Ian Goodfellow, Yoshua Bengio, Aaron Courville — Deep Learning

Ian Goodfellow, Yoshua Bengio, Aaron Courville — Deep Learning

Ian Goodfellow, Yoshua Bengio, Aaron Courville — Deep Learning

Ian Goodfellow,Yoshua Bengio, Aaron Courville — Deep Learning

Ian Goodfellow, Yoshua Bengio, Aaron Courville — Deep Learning Book

Ian Goodfellow, Yoshua Bengio, Aaron Courville — Deep Learning

— Ieee Artificial Neural Networks A Tutorial

Anil K. Jain, Jianchang Mao — Artificial Intelligence - IEEE Artificial Neural Networks A Tutorial

Jain — Artificial Neural Networks - A Tutorial

Unknown — Ian Goodfellow Yoshua Bengio Aaron Courville-Deep

Unknown Author — DeepLearningBook

John Hertz; Anders Krogh; Richard G Palmer — Introduction to the theory of neural computation

James A. Freeman, David M. Skapura — Neural Networks: Algorithms, Applications, and Programming Techniques

John A. Hertz, Anders S. Krogh, Richard G. Palmer — Introduction To The Theory Of Neural Computation, Volume I (Santa Fe Institute Series)

James A. Anderson — An Introduction to Neural Networks

Ian Cloete, Jacek M. Zurada — Knowledge-Based Neurocomputing

Ian Goodfellow, Yoshua Bengio, Aaron Courville — Deep Learning

Russell Reed, Robert J MarksII — Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks

Ian Goodfellow & Yoshua Bengio & Aaron Courville [Goodfellow, Ian & Bengio, Yoshua & Courville, Aaron] — Deep Learning (Adaptive Computation and Machine Learning series)

Saad David — On-Line Learning in Neural Networks

Larry Medsker, Lakhmi C. Jain — Recurrent Neural Networks

关键词