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Practical Automated Machine Learning Using H2O.ai

You're reading from   Practical Automated Machine Learning Using H2O.ai Discover the power of automated machine learning, from experimentation through to deployment to production

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781801074520
Length 396 pages
Edition 1st Edition
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Author (1):
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Salil Ajgaonkar Salil Ajgaonkar
Author Profile Icon Salil Ajgaonkar
Salil Ajgaonkar
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Table of Contents (19) Chapters Close

Preface 1. Part 1 H2O AutoML Basics
2. Chapter 1: Understanding H2O AutoML Basics FREE CHAPTER 3. Chapter 2: Working with H2O Flow (H2O’s Web UI) 4. Part 2 H2O AutoML Deep Dive
5. Chapter 3: Understanding Data Processing 6. Chapter 4: Understanding H2O AutoML Architecture and Training 7. Chapter 5: Understanding AutoML Algorithms 8. Chapter 6: Understanding H2O AutoML Leaderboard and Other Performance Metrics 9. Chapter 7: Working with Model Explainability 10. Part 3 H2O AutoML Advanced Implementation and Productization
11. Chapter 8: Exploring Optional Parameters for H2O AutoML 12. Chapter 9: Exploring Miscellaneous Features in H2O AutoML 13. Chapter 10: Working with Plain Old Java Objects (POJOs) 14. Chapter 11: Working with Model Object, Optimized (MOJO) 15. Chapter 12: Working with H2O AutoML and Apache Spark 16. Chapter 13: Using H2O AutoML with Other Technologies 17. Index 18. Other Books You May Enjoy

Technical requirements

All code examples in this chapter are run on Jupyter Notebook for an easy understanding of what each line in the code block does. You can run the whole block of code via a Python or R script executor and observe the output results, or you can follow along by installing Jupyter Notebook and observing the execution results of every line in the code blocks.

To install Jupyter Notebook, make sure you have the latest version of Python and pip installed on your system and execute the following command:

pip install jupyterlab

Once JupyterLab has successfully installed, you can start your Jupyter Notebook locally by executing the following command in your terminal:

jupyter notebook

This will open the Jupyter Notebook page on your default browser. You can then select which language you want to use and start executing the lines in the code step by step.

All code examples for this chapter can be found on GitHub at https://github.com/PacktPublishing/Practical...

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