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Comet for Data Science

You're reading from   Comet for Data Science Enhance your ability to manage and optimize the life cycle of your data science project

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Product type Paperback
Published in Aug 2022
Publisher Packt
ISBN-13 9781801814430
Length 402 pages
Edition 1st Edition
Tools
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Author (1):
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Angelica Lo Duca Angelica Lo Duca
Author Profile Icon Angelica Lo Duca
Angelica Lo Duca
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Table of Contents (16) Chapters Close

Preface 1. Section 1 – Getting Started with Comet
2. Chapter 1: An Overview of Comet FREE CHAPTER 3. Chapter 2: Exploratory Data Analysis in Comet 4. Chapter 3: Model Evaluation in Comet 5. Section 2 – A Deep Dive into Comet
6. Chapter 4: Workspaces, Projects, Experiments, and Models 7. Chapter 5: Building a Narrative in Comet 8. Chapter 6: Integrating Comet into DevOps 9. Chapter 7: Extending the GitLab DevOps Platform with Comet 10. Section 3 – Examples and Use Cases
11. Chapter 8: Comet for Machine Learning 12. Chapter 9: Comet for Natural Language Processing 13. Chapter 10: Comet for Deep Learning 14. Chapter 11: Comet for Time Series Analysis 15. Other Books You May Enjoy

Summary

We just completed our first steps in the journey of getting started with Comet!

Throughout this chapter, we described the motivation and purpose of the Comet platform, as well as how to get started with it. We showed that Comet can be used in almost all the steps of a data science project.

We also illustrated the concepts of workspaces, projects, experiments, and panels, and we set up the environment to work with Comet. Finally, we implemented two practical examples to get familiar with Comet.

Now that you have learned the basic concepts and we have set up the environment, we can move on to more specific and complex features provided by Comet.

In the next chapter, we will review some concepts about EDA and how to perform it in Comet.

You have been reading a chapter from
Comet for Data Science
Published in: Aug 2022
Publisher: Packt
ISBN-13: 9781801814430
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