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Full Description
This beginner's book will teach you how to apply the principles of data science to improve your business strategies - no math proficiency required! Easy-to-follow chapters take the reader through concepts like A/B testing, supervised and unsupervised machine learning, web scraping, and more. Each concept is illustrated using real-world business applications, real-world data, and useful Python code examples. The tone is conversational, and the author avoids the dense mathematical theories associated with data science in favour of simple explanations and practical applications. By the end of the book, readers should be comfortable working with data, applying data to business problems, and using best practices to analyse data using Python.
Contents
Acknowledgments
Introduction
Chapter 1: Exploratory Data Analysis
Chapter 2: Forecasting
Chapter 3: Group Comparisons
Chapter 4: A/B Testing
Chapter 5: Binary Classification
Chapter 6: Supervised Learning
Chapter 7: Unsupervised Learning
Chapter 8: Web Scraping
Chapter 9: Recommendation Systems
Chapter 10: Natural Language Processing
Chapter 11: Data Science in Other Languages
Index
