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Hands-On Machine Learning with IBM Watson

You're reading from   Hands-On Machine Learning with IBM Watson Leverage IBM Watson to implement machine learning techniques and algorithms using Python

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789611854
Length 288 pages
Edition 1st Edition
Languages
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Author (1):
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James D. Miller James D. Miller
Author Profile Icon James D. Miller
James D. Miller
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Toc

Table of Contents (15) Chapters Close

Preface 1. Section 1: Introduction and Foundation FREE CHAPTER
2. Introduction to IBM Cloud 3. Feature Extraction - A Bag of Tricks 4. Supervised Machine Learning Models for Your Data 5. Implementing Unsupervised Algorithms 6. Section 2: Tools and Ingredients for Machine Learning in IBM Cloud
7. Machine Learning Workouts on IBM Cloud 8. Using Spark with IBM Watson Studio 9. Deep Learning Using TensorFlow on the IBM Cloud 10. Section 3: Real-Life Complete Case Studies
11. Creating a Facial Expression Platform on IBM Cloud 12. The Automated Classification of Lithofacies Formation Using ML 13. Building a Cloud-Based Multibiometric Identity Authentication Platform 14. Another Book You May Enjoy

Deep Learning Using TensorFlow on the IBM Cloud

In this chapter, we will provide an introduction to the concepts of deep learning and neural networks on the IBM Cloud. An overview of how to use the TensorFlow framework to implement deep learning models on the cloud will be provided as well. This chapter is designed to be a balance between theory and practical implementation.

We will cover the following topics in this chapter:

  • Introduction to deep learning
  • TensorFlow basics
  • Neural networks using TensorFlow
  • An example
  • TensorFlow and image classifications
  • Additional preparation
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