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Introduction to deep learning / Eugene Charniak

By: Material type: TextTextPublication details: Cambridge, Massachusetts : The MIT Press, c2018Description: xii, 174 pages : illustrations ; 23 cmISBN:
  • 9780262039512
Subject(s): LOC classification:
  • Q 325.7 .C43 2018
Contents:
Feed-forward neural nets -- Tensorflow -- Convolutional neural networks -- Word embeddings and recurrent NNs -- Sequence-to-sequence learning -- Deep reinforcement learning -- Unsupervised neural-network models.
Summary: This concise, project-driven guide to deep learning takes readers through a series of program-writing tasks that introduce them to the use of deep learning in such areas of artificial intelligence as computer vision, natural-language processing, and reinforcement learning.
Item type: Books
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Item type Current library Home library Collection Call number Copy number Status Date due Barcode
Books Books National University - Manila LRC - Main General Circulation Machine Learning GC Q 325.7 .C43 2018 (Browse shelf(Opens below)) c.1 Available NULIB000017776

Includes bibliographical references and index.

Feed-forward neural nets -- Tensorflow -- Convolutional neural networks -- Word embeddings and recurrent NNs -- Sequence-to-sequence learning -- Deep reinforcement learning -- Unsupervised neural-network models.

This concise, project-driven guide to deep learning takes readers through a series of program-writing tasks that introduce them to the use of deep learning in such areas of artificial intelligence as computer vision, natural-language processing, and reinforcement learning.

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