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Fundamentals of deep learning : designing next-generation machine intelligence algorithms

By: Buduma, Nikhil.
Contributor(s): Locascio, Nicholas.
Material type: materialTypeLabelBookPublisher: New Delhi : O'Reilly, ©2017Description: xii, 283 p. : ill.; 24 cm.ISBN: 9789352135608.Subject(s): Artificial intelligence | Machine learning | Neural networks (Computer science) | Artificial intelligence | Machine learning | Neural networks (Computer science) | Deep learning | Künstliche Intelligenz | Maschinelles Lernen
Contents:
The neural network -- Training feed-forward neural networks -- Implementing neural networks in TensorFlow -- Beyond gradient descent -- Convolutional neural networks -- Embedding and representation learning -- Models for sequence analysis -- Memory augmented neural networks -- Deep reinforcement learning.
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Computer Science and Engineering CB 006.31 BUD-F (Browse shelf) Not For Loan 008756
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Computer Science and Engineering 006.31 BUD-F (Browse shelf) Checked out 21/10/2019 008720
Books Books IIITD
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Computer Science and Engineering REF 006.31 BUD-F (Browse shelf) Checked out Not For Loan 24/10/2019 008721
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CB 005.7 ACH-B Big data and analytics CB 005.74 WHI-H Hadoop : CB 006 CON-M Machine learning for hackers CB 006.31 BUD-F Fundamentals of deep learning : CB 006.31 KIR-T Thoughtful machine learning with Python : CB 006.312 WIC-R R for data science : CBIA 005.75 PRA-D Data warehouse requirements engineering :

Includes bibliographical references and index.

The neural network -- Training feed-forward neural networks -- Implementing neural networks in TensorFlow -- Beyond gradient descent -- Convolutional neural networks -- Embedding and representation learning -- Models for sequence analysis -- Memory augmented neural networks -- Deep reinforcement learning.

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