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Introduction to Deep Learning Business Applications for Developers From Conversational Bots in Customer Service to Medical Image Processing

Title
Introduction to Deep Learning Business Applications for Developers [electronic resource] : From Conversational Bots in Customer Service to Medical Image Processing / by Armando Vieira, Bernardete Ribeiro.
ISBN
9781484234532
Publication
Berkeley, CA : Apress : Imprint: Apress, 2018.
Physical Description
1 online resource (XXI, 343 p.) 64 illus.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and annotation, video processing and annotation, voice recognition, intelligent personal assistants, automated translation, and autonomous vehicles. An Introduction to Deep Learning Business Applications for Developers covers some common DL algorithms such as content-based recommendation algorithms and natural language processing. You’ll explore examples, such as video prediction with fully convolutional neural networks (FCNN) and residual neural networks (ResNets). You will also see applications of DL for controlling robotics, exploring the DeepQ learning algorithm with Monte Carlo Tree search (used to beat humans in the game of Go), and modeling for financial risk assessment. There will also be mention of the powerful set of algorithms called Generative Adversarial Neural networks (GANs) that can be applied for image colorization, image completion, and style transfer. After reading this book you will have an overview of the exciting field of deep neural networks and an understanding of most of the major applications of deep learning. The book contains some coding examples, tricks, and insights on how to train deep learning models using the Keras framework. You will: Find out about deep learning and why it is so powerful Work with the major algorithms available to train deep learning models See the major breakthroughs in terms of applications of deep learning Run simple examples with a selection of deep learning libraries Discover the areas of impact of deep learning in business.
Variant and related titles
Springer ebooks.
Other formats
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
May 09, 2018
Contents
1 Introduction
2 Deep Learning: An Overview
3 Deep Neural Network Models
4 Image Processing
5 Natural Language Processing and Speech
6 Reinforcement Learning and Robotics
7 Recommendations Algorithms and Advertising
8 Games and Art
9 Other Applications
10 Business Impact of DL Technology
11 New Research and Future Directions
Appendix Training DNN with Keras.
Also listed under
Ribeiro, Bernardete.
SpringerLink (Online service)
Citation

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