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Machine Learning with TensorFlow 1.x

You're reading from   Machine Learning with TensorFlow 1.x Second generation machine learning with Google's brainchild - TensorFlow 1.x

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781786462961
Length 304 pages
Edition 1st Edition
Languages
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Authors (3):
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Saif Ahmed Saif Ahmed
Author Profile Icon Saif Ahmed
Saif Ahmed
Quan Hua Quan Hua
Author Profile Icon Quan Hua
Quan Hua
Shams Ul Azeem Shams Ul Azeem
Author Profile Icon Shams Ul Azeem
Shams Ul Azeem
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with TensorFlow FREE CHAPTER 2. Your First Classifier 3. The TensorFlow Toolbox 4. Cats and Dogs 5. Sequence to Sequence Models-Parlez-vous Français? 6. Finding Meaning 7. Making Money with Machine Learning 8. The Doctor Will See You Now 9. Cruise Control - Automation 10. Go Live and Go Big 11. Going Further - 21 Problems 12. Advanced Installation

What this book covers

Chapter 1, Getting Started with TensorFlow, shows how to install Tensorflow and get started on Ubuntu, macOS, and Windows.

Chapter 2, Your First Classifier, guides you through your first journey with a handwriting recognizer.

Chapter 3, The TensorFlow Toolbox, gives you an overview of the tools that Tensorflow provides to work more effectively and easily.

Chapter 4, Cats and Dogs, teaches you how to build an image classifier using Convolutional Neural Networks in TensorFlow.

Chapter 5, Sequence to Sequence Models—Parlez-vous Français?, discusses how to build an English to French translator using sequence-to-sequence models.

Chapter 6, Finding Meaning, explores the ways to find the meaning in the text by using sentiment analysis, entity extraction, keyword extraction, and word-relation extraction.

Chapter 7, Making Money with Machine Learning, dives into an area with copious amounts of data: the financial world. You will learn how to work with the time series data to solve the financial problems.

Chapter 8, The Doctor Will See You Now, investigates ways to tackle an enterprise-grade problem—medical diagnosis—using deep neural networks.

Chapter 9, Cruise Control - Automation, teaches you how to create a production system, ranging from training to serving a model. The system can also receive user feedbacks and automatically train itself every day.

Chapter 10, Go Live and Go Big, guides you through the world of Amazon Web Services and shows you how to take advantage of a multiple GPUs system on Amazon servers.

Chapter 11, Going Further - 21 Problems, introduces 21 real-life problems that you can use in deep learning—TensorFlow to solve after reading this book.

Appendix, Advanced Installation, discusses GPUs and focuses on a step-by-step CUDA setup and a GPU-based TensorFlow installation.

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