Book Detail

Python Deep Learning Cookbook

Author(s)
: Indra den Bakker
Edition
:
Call Number
: 005.262 BAK p
ISBN/ISSN
: 978-1-78712-519-3
Subject(s)
: Python
Clasification
: 005.262 BAK p
Series Title
:
GMD
: Buku
Language
: English
Publisher
: Packt Pubishing Ltd
Publishing Year
: 2017
Publishing Place
: BIRMINGHAM
Collation
: 14 chapter; Illus; 25 cm
Specific Detail Info
:
File Attachment
: No Attachment
Availibilty
: B003339.1   My Library   : Available
The Python Deep Learning Cookbook presents technical solutions to the issues presented, along with a detailed explanation of the solutions. Furthermore, a discussion on corresponding pros and cons of implementing the proposed solution using one of the popular frameworks like TensorFlow, PyTorch, Keras and CNTK is provided. The book includes recipes that are related to the basic concepts of neural networks. All techniques s, as well as classical networks topologies. The main purpose of this book is to provide Python programmers a detailed list of recipes to apply deep learning to common and not-so-common scenarios. This book provides a top-down and bottom-up approach to demonstrate deep learning solutions to real-world problems in different areas. These applications include Computer Vision, Natural Language Processing, Time Series, and Robotics.

The Python Deep Learning Cookbook presents technical solutions to the issues presented, along with a detailed explanation of the solutions. Furthermore, a discussion on corresponding pros and cons of implementing the proposed solution using one of the popular frameworks like TensorFlow, PyTorch, Keras and CNTK is provided. The book includes recipes that are related to the basic concepts of neural networks. All techniques s, as well as classical networks topologies. The main purpose of this book is to provide Python programmers a detailed list of recipes to apply deep learning to common and not-so-common scenarios. This book provides a top-down and bottom-up approach to demonstrate deep learning solutions to real-world problems in different areas. These applications include Computer Vision, Natural Language Processing, Time Series, and Robotics.

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