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Hands-On Machine Learning with IBM Watson

You're reading from  Hands-On Machine Learning with IBM Watson

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

Table of Contents (15) Chapters close

Preface 1. Section 1: Introduction and Foundation
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

Watson Studio and Python

As already mentioned, Python could very well be (currently anyway) the programming or scripting language most often chosen for predictive modeling and data science projects. A significant advance in the area of this type of computing is Jupyter Notebook (formerly, IPython) technology.

A Jupyter Notebook is a web-based environment aimed at interactive computing where you can run small bits of code to process data, and immediately view the results of that code. Notebooks include all of the building blocks you need to work with data:

  • The data
  • The code computations that process the data
  • Visualizations of the results (of the code computations)
  • Text and rich media to enhance your understanding

In addition, saved notebooks record how you worked with data, so you can more readily understand precisely what was done, reproduce those computations consistently...

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