You're reading from Agile Machine Learning with DataRobot Automate each step of the machine learning life cycle, from understanding problems to delivering value

Product type Paperback

Published in Dec 2021

Publisher Packt

ISBN-13 9781801076807

Length 344 pages

Edition 1st Edition

Languages

Python

Tools

Datarobot

Concepts

Agile

Authors (2):

Bipin Chadha

Sylvester Juwe

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Table of Contents (19) Chapters

Preface

1. Section 1: Foundations

2. Chapter 1: What Is DataRobot and Why You Need It? FREE CHAPTER

3. Chapter 2: Machine Learning Basics

4. Chapter 3: Understanding and Defining Business Problems

5. Section 2: Full ML Life Cycle with DataRobot: Concept to Value

6. Chapter 4: Preparing Data for DataRobot

7. Chapter 5: Exploratory Data Analysis with DataRobot

8. Chapter 6: Model Building with DataRobot

9. Chapter 7: Model Understanding and Explainability

10. Chapter 8: Model Scoring and Deployment

11. Section 3: Advanced Topics

12. Chapter 9: Forecasting and Time Series Modeling

13. Chapter 10: Recommender Systems

14. Chapter 11: Working with Geospatial Data, NLP, and Image Processing

15. Chapter 12: DataRobot Python API

16. Chapter 13: Model Governance and MLOps

17. Chapter 14: Conclusion

18. Other Books You May Enjoy

Technical requirements

Most parts of this chapter require access to the DataRobot software. The code example is based on a relatively small dataset, Book-Crossing, consisting of three tables, whose manipulation was carried out with Jupyter Notebook.

Check out the following video to see the Code in Action at https://bit.ly/3HxcNUL.

Book-Crossing dataset

The example used to illustrate the use of DataRobot in building recommendation systems is based on the Book-Crossing dataset by Cai-Nicolas Ziegler and colleagues. This dataset was accessed at http://www2.informatik.uni-freiburg.de/~cziegler/BX/.

Note

Before using this dataset, the authors of this book have informed the owner of the dataset about its use in this book.

Cai-Nicolas Ziegler, Sean M. McNee, Joseph A. Konstan, Georg Lausen (2005). Improving Recommendation Lists Through Topic Diversification. Proceedings of the 14th International World Wide Web Conference (WWW '05). May 10 – 14, 2005, Chiba...

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You're reading from Agile Machine Learning with DataRobot Automate each step of the machine learning life cycle, from understanding problems to delivering value

Table of Contents (19) Chapters

Technical requirements

Book-Crossing dataset

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Authors (2)

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