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Data Science for Decision Makers

You're reading from   Data Science for Decision Makers Enhance your leadership skills with data science and AI expertise

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781837637294
Length 270 pages
Edition 1st Edition
Languages
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Author (1):
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Jon Howells Jon Howells
Author Profile Icon Jon Howells
Jon Howells
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Table of Contents (20) Chapters Close

Preface 1. Part 1: Understanding Data Science and Its Foundations
2. Chapter 1: Introducing Data Science FREE CHAPTER 3. Chapter 2: Characterizing and Collecting Data 4. Chapter 3: Exploratory Data Analysis 5. Chapter 4: The Significance of Significance 6. Chapter 5: Understanding Regression 7. Part 2: Machine Learning – Concepts, Applications, and Pitfalls
8. Chapter 6: Introducing Machine Learning 9. Chapter 7: Supervised Machine Learning 10. Chapter 8: Unsupervised Machine Learning 11. Chapter 9: Interpreting and Evaluating Machine Learning Models 12. Chapter 10: Common Pitfalls in Machine Learning 13. Part 3: Leading Successful Data Science Projects and Teams
14. Chapter 11: The Structure of a Data Science Project 15. Chapter 12: The Data Science Team 16. Chapter 13: Managing the Data Science Team 17. Chapter 14: Continuing Your Journey as a Data Science Leader 18. Index 19. Other Books You May Enjoy

Navigating the landscape of emerging technologies

The rate of progress within data science, machine learning, and artificial intelligence is incredibly fast. Groundbreaking research papers come out weekly, state-of-the-art large language models come out every month, and deep learning frameworks are released every month. It can feel hard to keep up. The landscape is vast and varied. Understanding it all is impossible.

Look at the visualization of tools and technologies within machine learning, artificial intelligence, and data for 2024 that follows. Attempting to learn about all of these technologies would be a mammoth task.

Figure 14.1: The 2024 machine learning, artificial intelligence, and data landscape

Figure 14.1: The 2024 machine learning, artificial intelligence, and data landscape

Staying up to date is a huge challenge. How can you stay current? How can you work on your career?

First, remember this: You don’t need to know everything. You don’t need to master every tool. Focus on what’s relevant to you...

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