For graduate-level neural network courses offered in the departments of Computer Engineering, Electrical Engineering, and Computer Science.

 

Buy Now From Amazon

Product Review

For graduate-level neural network courses offered in the departments of Computer Engineering, Electrical Engineering, and Computer Science.

 

Neural Networks and Learning Machines, Third Edition is renowned for its thoroughness and readability. This well-organized and completely up-to-date text remains the most comprehensive treatment of neural networks from an engineering perspective. This is ideal for professional engineers and research scientists.

 

Matlab codes used for the computer experiments in the text are available for download at: http://www.pearsonhighered.com/haykin/

 

Refocused, revised and renamed to reflect the duality of neural networks and learning machines, this edition recognizes that the subject matter is richer when these topics are studied together. Ideas drawn from neural networks and machine learning are hybridized to perform improved learning tasks beyond the capability of either independently.



Similar Products

Deep Learning (Adaptive Computation and Machine Learning series)The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)Pattern Recognition and Machine Learning (Information Science and Statistics)Mastering MATLABNeural Network Design (2nd Edition)Python Machine LearningArtificial Intelligence: A Modern Approach (3rd Edition)Bayesian Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science)Introduction to Algorithms, 3rd Edition (MIT Press)Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems