Data Science for Decision Makers
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Data Science for Decision Makers

Enhance your leadership skills with data science and AI expertise

About the Book

As data science and artificial intelligence (AI) become prevalent across industries, executives without formal education in statistics and machine learning, as well as data scientists moving into leadership roles, must learn how to make informed decisions about complex models and manage data teams. This book will elevate your leadership skills by guiding you through the core concepts of data science and AI.

This comprehensive guide is designed to bridge the gap between business needs and technical solutions, empowering you to make informed decisions and drive measurable value within your organization. Through practical examples and clear explanations, you'll learn how to collect and analyze structured and unstructured data, build a strong foundation in statistics and machine learning, and evaluate models confidently. By recognizing common pitfalls and valuable use cases, you'll plan data science projects effectively, from the ground up to completion. Beyond technical aspects, this book provides tools to recruit top talent, manage high-performing teams, and stay up to date with industry advancements.

By the end of this book, you’ll be able to characterize the data within your organization and frame business problems as data science problems.

About the Author

Packt Publishing Ltd
Packt Publishing Ltd

Packt Publishing are an established global technical learning content provider, founded in Birmingham, UK with over twenty years’ experience in delivering premium rich content from ground-breaking authors on a wide range of emerging and popular technologies. Our titles have global relevance our multimedia portfolio includes over 9,000 books, e-books, audiobooks and video courses. www.packtpub.com

Table of Contents

  1. Introducing Data Science
  2. Characterizing and Collecting Data
  3. Exploratory Data Analysis
  4. The Significance of Significance
  5. Understanding Regression
  6. Introducing Machine Learning
  7. Supervised Machine Learning
  8. Unsupervised Machine Learning
  9. Interpreting and Evaluating Machine Learning Models
  10. Common Pitfalls in Machine Learning
  11. The Structure of a Data Science Project
  12. The Data Science Team
  13. Managing the Data Science Team
  14. Continuing Your Journey as a Data Science Leader

About the Publisher

This book is published on Leanpub by Packt Publishing Ltd

Packt Publishing are an established global technical learning content provider, founded in Birmingham, UK with over twenty years’ experience in delivering premium rich content from ground-breaking authors on a wide range of emerging and popular technologies. Our titles have global relevance our multimedia portfolio includes over 9,000 books, e-books, audiobooks and video courses. www.packtpub.com

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