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Managing Data Science

You're reading from   Managing Data Science Effective strategies to manage data science projects and build a sustainable team

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Product type Paperback
Published in Nov 2019
Publisher Packt
ISBN-13 9781838826321
Length 290 pages
Edition 1st Edition
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Author (1):
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Kirill Dubovikov Kirill Dubovikov
Author Profile Icon Kirill Dubovikov
Kirill Dubovikov
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Toc

Table of Contents (18) Chapters Close

1. Section 1: What is Data Science?
2. What You Can Do with Data Science FREE CHAPTER 3. Testing Your Models 4. Understanding AI 5. Section 2: Building and Sustaining a Team
6. An Ideal Data Science Team 7. Conducting Data Science Interviews 8. Building Your Data Science Team 9. Section 3: Managing Various Data Science Projects
10. Managing Innovation 11. Managing Data Science Projects 12. Common Pitfalls of Data Science Projects 13. Creating Products and Improving Reusability 14. Section 4: Creating a Development Infrastructure
15. Implementing ModelOps 16. Building Your Technology Stack 17. Conclusion 18. Other Books You May Enjoy

Building Your Technology Stack

Technology choices have lasting consequences. A project's technology stack determines the functional and nonfunctional capabilities of your system, so it is critical to make thoughtful choices. The bidirectional link between technologies and requirements opens up an analytical approach for choosing between different technologies by matching their features against the project's needs. In this chapter, we will see how we can use software design practices to form project-specific technology stacks and see what technologies should constitute the core technology stack that's shared among all of your projects. We will also explore an approach that compares different technologies so that you can make a rational choice between apparently similar options.

In this chapter, we will cover the following topics:

  • Defining the elements of the technology...
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