Islamic University of Technology OPAC


Image from Coce

Deep learning / Ian Goodfellow, Yoshua Bengio, and Aaron Courville.

By: Contributor(s): Material type: TextTextSeries: Adaptive computation and machine learningPublisher: Cambridge, Massachusetts : The MIT Press, [2016]Copyright date: ©2016Description: xxii, 775 pages : illustrations (some color) ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780262035613
  • 0262035618
Subject(s): DDC classification:
  • 006.31 23
LOC classification:
  • Q325.5 .G66 2016
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.
Item type: Books
Holdings
Item type Current library Shelving location Call number Copy number Status Date due Barcode Item holds
Books IUT Library General Stacks 006.31 GOD 01 Checked out 03/23/2026 0000045476
Books IUT Library General Stacks 006.31 GOD 02 Available 0000045477
Books IUT Library General Stacks 006.31 GOD 03 Available 0000045478
Books IUT Library General Stacks 006.31 GOD 04 Available 0000045479
Books IUT Library General Stacks 006.31 GOD 05 Available 0000045480
Books IUT Library General Stacks 006.31 GOD 06 Available 0000045481
Books IUT Library General Stacks 006.31 GOD 07 Checked out 08/03/2026 0000045482
Books IUT Library General Stacks 006.31 GOD 08 Checked out 04/18/2026 0000045483
Books IUT Library General Stacks 006.31 GOD 09 Checked out 04/28/2026 0000045484
Books IUT Library General Stacks 006.31 GOD 10 Checked out 03/28/2026 0000045485
Total holds: 0

Includes bibliographical references (pages 711-766) and index.

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.

© 2025 | Library, Islamic University of Technology