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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? FREE CHAPTER
2. What You Can Do with Data Science 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

Creating Products and Improving Reusability

In this chapter, we will conclude the Managing Data Science Projects section by looking at how we can help products grow and improve reusability. This chapter focuses on teams who work to deliver custom solutions for customers. You will find the content in this chapter helpful if your team helps internal business stakeholders at the company or external customers who want to buy expertise, services, and software solutions. The benefits of product thinking and reusability are underappreciated when it comes to the consultation stage, whereas they become more obvious if your team is developing a product that is focused on a market niche.

In this chapter, we will cover the following topics:

  • Thinking of projects as products
  • Determining the stage of your project
  • Improving reusability
  • Seeking and building products
...
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