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Neural Networks and Deep Learning: A Textbook - Research Book

Neural Networks and Deep Learning: A Textbook - Research Book

Good Research Book in Neural Networks and Deep Learning: A Textbook

Author(s) Name:  Charu C. Aggarwal

About the Book:

   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 understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec.

Table of Contents

  • An Introduction to Neural Networks
  • Machine Learning with Shallow Neural Networks
  • Training Deep Neural Networks
  • Teaching Deep Learners to Generalize
  • Radial Basis Function Networks
  • Restricted Boltzmann Machines
  • Recurrent Neural Networks
  • Convolutional Neural Networks
  • Deep Reinforcement Learning

    • ISBN:   978-3-319-94463-0

    Publisher:  Springer

    Year of Publication:  2018

    Book Link:  Home Page Url