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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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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

What You Can Do with Data Science

I once told a friend who works as a software developer about one of the largest European data science conferences. He showed genuine interest and asked whether we could go together. Sure, I said. Let's broaden our knowledge together. It will be great to talk to you about machine learning. Several days later, we were sitting in the middle of a large conference hall. The first speaker had come on stage and told us about some technical tricks he used to win several data science competitions. When the next speaker talked about tensor algebra, I noticed a depleted look in the eyes of my friend.

What's up? I asked.

I'm just wondering when they'll show us the robots.

To avoid having incorrect expectations, we need to inform ourselves. Before building a house, you'd better know how a hammer works. Having basic...

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