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Agile Machine Learning with DataRobot

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

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Product type Paperback
Published in Dec 2021
Publisher Packt
ISBN-13 9781801076807
Length 344 pages
Edition 1st Edition
Languages
Concepts
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Authors (2):
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Bipin Chadha Bipin Chadha
Author Profile Icon Bipin Chadha
Bipin Chadha
Sylvester Juwe Sylvester Juwe
Author Profile Icon Sylvester Juwe
Sylvester Juwe
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Table of Contents (19) Chapters Close

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

Configuring a modeling project

In the previous chapter, we created a project and performed data analysis. We also saw that DataRobot automatically built several models for us. To build these models, we used default project settings.

In this section, we will cover what DataRobot did for us by default and look at how we can fine-tune that behavior. If you remember, once we click the Start button on the project page (see Figure 5.1 in Chapter 5, Exploratory Data Analysis with DataRobot), we cannot make any changes to the project options. We will therefore create a new project to review and select the options we want.

For this, let's go into DataRobot and select the Create New Project menu option. Just as before, we will now upload the same automobile dataset file that we used before. This time, you can name the project Automobile Example 2, as illustrated in the following screenshot:

Figure 6.1 – Uploading the dataset for a new project

You can...

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