Neural Networks: A Comprehensive Foundation (2nd Edition)

Provides a comprehensive foundation of neural networks, recognizing the multidisciplinary nature of the subject, supported with examples, computer-oriented experiments, end of chapter problems, and a bibliography. DLC: Neural networks (Computer science).

• Neural Networks and Deep Learning: A Textbook
• Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series)
• The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
• Convex Optimization
• Neural Networks and Learning Machines (3rd Edition)
• Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)
• An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
• Neural Networks: A Comprehensive Foundation
• Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
• Pattern Classification (Pt.1)