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The Art of Data-Driven Business
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The Art of Data-Driven Business
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Overview of this book
One of the most valuable contributions of data science is toward helping businesses make the right decisions. Understanding this complicated confluence of two disparate worlds, as well as a fiercely competitive market, calls for all the guidance you can get.
The Art of Data-Driven Business is your invaluable guide to gaining a business-driven perspective, as well as leveraging the power of machine learning (ML) to guide decision-making in your business. This book provides a common ground of discussion for several profiles within a company.
You’ll begin by looking at how to use Python and its many libraries for machine learning. Experienced data scientists may want to skip this short introduction, but you’ll soon get to the meat of the book and explore the many and varied ways ML with Python can be applied to the domain of business decisions through real-world business problems that you can tackle by yourself. As you advance, you’ll gain practical insights into the value that ML can provide to your business, as well as the technical ability to apply a wide variety of tried-and-tested ML methods.
By the end of this Python book, you’ll have learned the value of basing your business decisions on data-driven methodologies and have developed the Python skills needed to apply what you’ve learned in the real world.
Table of Contents (17 chapters)
Preface
Part 1: Data Analytics and Forecasting with Python
Chapter 1: Analyzing and Visualizing Data with Python
Chapter 2: Using Machine Learning in Business Operations
Part 2: Market and Customer Insights
Chapter 3: Finding Business Opportunities with Market Insights
Chapter 4: Understanding Customer Preferences with Conjoint Analysis
Chapter 5: Selecting the Optimal Price with Price Demand Elasticity
Chapter 6: Product Recommendation
Part 3: Operation and Pricing Optimization
Chapter 7: Predicting Customer Churn
Chapter 8: Grouping Users with Customer Segmentation
Chapter 9: Using Historical Markdown Data to Predict Sales
Chapter 10: Web Analytics Optimization
Chapter 11: Creating a Data-Driven Culture in Business
Index
Customer Reviews