Fundamentals of deep learning :

By: Buduma, NikhilContributor(s): Locascio, NicholasMaterial type: TextTextPublication details: Mumbai : Shroff Publishers, 2017Edition: First editionDescription: xii, 283 pages : illustrations (some color)ISBN: 9781491925614; 9789352135608Subject(s): Artificial intelligence | Machine learning | Neural networks (Computer science) | Deep learning | Maschinelles LernenDDC classification: 006.31
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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Originally published in Sebastopol, CA. by O'Reilly Media,

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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