Neural Networks and Deep Learning A Textbook /

• Main Author: Aggarwal, Charu C. (Author, http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Subjects: Artificial intelligence.; Computers.; Microprocessors.; Artificial Intelligence.; Information Systems and Communication Service.; Processor Architectures.

This book covers both classical and modern models in deep learning. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on under...

Table of Contents:

• 1 An Introduction to Neural Networks
• 2 Machine Learning with Shallow Neural Networks
• 3 Training Deep Neural Networks
• 4 Teaching Deep Learners to Generalize
• 5 Radical Basis Function Networks
• 6 Restricted Boltzmann Machines
• 7 Recurrent Neural Networks
• 8 Convolutional Neural Networks
• 9 Deep Reinforcement Learning
• 10 Advanced Topics in Deep Learning.