Fundamentals of deep learning : designing next-generation machine intelligence algorithms / Nikhil Buduma ; with contributions by Nicholas Locascio.

By: Buduma, Nikhil [author.]Contributor(s): Locascio, Nicholas [author.]Material type: TextTextPublisher: Sebastopol, CA : O'Reilly Media, 2017Edition: 1st edDescription: 283 p: illustrations (some color) ; 24 cmISBN: 9781491925614; 1491925612Other title: Designing next-generation machine intelligence algorithmsSubject(s): Artificial intelligence | Machine learning | Neural networks (Computer science) | Artificial intelligence | Machine learning | Neural networks (Computer science) | Deep learning | Künstliche Intelligenz | Maschinelles LernenDDC classification: 006.31 LOC classification: TA347.A78 | B83 2017
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.
Summary: In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. If you're familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started.
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Item type Current library Call number Status Date due Barcode Item holds
Books Books Namal Library
Computer Science 		006.3/1 BUD-F 2017 14272 (Browse shelf (Opens below)) Available 0014272
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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.

In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. If you're familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started.

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