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Deep Learning with TensorFlow

You're reading from Deep Learning with TensorFlow Explore neural networks and build intelligent systems with Python

Product type Paperback

Published in Mar 2018

Publisher Packt

ISBN-13 9781788831109

Length 484 pages

Edition 2nd Edition

Languages

Python

Tools

TensorFlow

Concepts

Deep Learning

Authors (2):

Giancarlo Zaccone

Md. Rezaul Karim

View More author details

Table of Contents (13) Chapters

Preface

1. Getting Started with Deep Learning FREE CHAPTER

2. A First Look at TensorFlow

3. Feed-Forward Neural Networks with TensorFlow

4. Convolutional Neural Networks

5. Optimizing TensorFlow Autoencoders

6. Recurrent Neural Networks

7. Heterogeneous and Distributed Computing

8. Advanced TensorFlow Programming

9. Recommendation Systems Using Factorization Machines

10. Reinforcement Learning

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Index

Index

A

activation functions
- about / Activation functions
- sigmoid / Using sigmoid
- tanh / Using tanh
- ReLU / Using ReLU
- softmax / Using softmax
AlexNet
- about / AlexNet
- architecture / AlexNet
Alternating Least Squares (ALS) algorithm
- about / Model-based collaborative filtering
- advantages / Model-based collaborative filtering
Amazon Web Services (AWS) / Deep learning frameworks
AMIs (Amazon Machine Images) / Deep learning frameworks
Area Under the Precision-Recall Curve (AUPRC) / Problem description
Artificial Neural Networks (ANNs)
- about / What is deep learning?, Artificial neural networks
- learning / How does an ANN learn?
- backpropagation algorithm / ANNs and the backpropagation algorithm
artificial neuron
- about / The artificial neuron
artistic style learning, with VGG-19
- about / Artistic style learning with VGG-19
autoencoder
- working / How does an autoencoder work?
- implementing, with TensorFlow / Implementing...

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Authors (2)

Zaccone

Zaccone

Giancarlo Zaccone has over fifteen years' experience of managing research projects in the scientific and industrial domains. He is a software and systems engineer at the European Space Agency (ESTEC), where he mainly deals with the cybersecurity of satellite navigation systems. Giancarlo holds a master's degree in physics and an advanced master's degree in scientific computing. Giancarlo has already authored the following titles, available from Packt: Python Parallel Programming Cookbook (First Edition), Getting Started with TensorFlow, Deep Learning with TensorFlow (First Edition), and Deep Learning with TensorFlow (Second Edition).

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Karim

Karim

Md. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning, knowledge graphs, and explainable artificial intelligence (XAI). Currently, he is working as a research scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he worked as a researcher at the Insight Centre for Data Analytics, Ireland. Previously, he worked as a lead software engineer at Samsung Electronics, Korea.

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