Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions

Nathaniel E. Helwig

Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions, authored by Nathaniel E. Helwig, is a comprehensive guide to unlocking the true potential of data using machine learning and economics in a business setting. This book aims to help readers better understand and utilize data to make informed business decisions that optimize the performance, automation, and acceleration of their organizations.

The book begins by introducing the fundamental principles of data science, machine learning, and economics. It then outlines how organizations can create data management and governance systems to ensure the data they collect is reliable, accurate, and secure. The author discusses the various data collection and analysis techniques businesses can use to turn their data into actionable insights. Readers will learn how to generate predictions, build recommendation systems, and create personalized experiences for their customers.

The latter half of the book is devoted to applying these concepts to real-world business cases. The author uses case studies from various industries, including finance, healthcare, and e-commerce, to demonstrate how businesses can apply data science to their everyday operations. Readers will learn how to build models to identify and mitigate fraud in financial institutions, analyze customer behavior to maximize profitability in e-commerce, and optimize healthcare delivery to improve patient outcomes.

Overall, Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions, is an excellent resource for anyone looking to leverage data to improve business performance. It provides comprehensive coverage of data science techniques and provides practical examples to help readers better understand how to apply them in their organizations.

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