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Deep Learning

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that...

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Bibliographic Details
Main Author: Ian Goodfellow
Other Authors: Yoshua Bengio; Aaron Courville
Format: Printed Book
Published: Cambridge, Massachusetts The MIT Press 2016
Series:Adaptive Computation and Machine Learning series
Subjects:
Table of Contents:
  • Applied math and machine learning basics. Linear algebra
  • Probability and information theory
  • Numerical computation
  • Machine learning basics
  • Deep networks: modern practices. Deep feedforward networks
  • Regularization for deep learning
  • Optimization for training deep models
  • Convolutional networks
  • Sequence modeling: recurrent and recursive nets
  • Practical methodology
  • Applications
  • Deep learning research. Linear factor models
  • Autoencoders
  • Representation learning
  • Structured probabilistic models for deep learning
  • Monte Carlo methods
  • Confronting the partition function
  • Approximate inference
  • Deep generative models.