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Book Overview & Buying
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Table Of Contents
Data Science for Decision Makers
By :
Data Science for Decision Makers
By:
Overview of this 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.
Table of Contents (20 chapters)
Preface
Part 1: Understanding Data Science and Its Foundations
Chapter 1: Introducing Data Science
Chapter 2: Characterizing and Collecting Data
Chapter 3: Exploratory Data Analysis
Chapter 4: The Significance of Significance
Chapter 5: Understanding Regression
Part 2: Machine Learning – Concepts, Applications, and Pitfalls
Chapter 6: Introducing Machine Learning
Chapter 7: Supervised Machine Learning
Chapter 8: Unsupervised Machine Learning
Chapter 9: Interpreting and Evaluating Machine Learning Models
Chapter 10: Common Pitfalls in Machine Learning
Part 3: Leading Successful Data Science Projects and Teams
Chapter 11: The Structure of a Data Science Project
Chapter 12: The Data Science Team
Chapter 13: Managing the Data Science Team
Chapter 14: Continuing Your Journey as a Data Science Leader
Index