Dive Into Data Science

Learn how to use data science and Python to solve everyday business problems.

Dive into the exciting world of data science with this practical introduction. Packed with essential skills and useful examples, Dive Into Data Science will show you how to obtain, analyze, and visualize data so you can leverage its power to solve common business challenges.

With only a basic understanding of Python and high school math, you’ll be able to effortlessly work through the book and start implementing data science in your day-to-day work. From improving a bike sharing company to extracting data from websites and creating recommendation systems, you’ll discover how to find and use data-driven solutions to make business decisions.

Topics covered include conducting exploratory data analysis, running A/B tests, performing binary classification using logistic regression models, and using machine learning algorithms.

You’ll also learn how to:

• Forecast consumer demand 
• Optimize marketing campaigns
• Reduce customer attrition
• Predict website traffic
• Build recommendation systems

With this practical guide at your fingertips, harness the power of programming, mathematical theory, and good old common sense to find data-driven solutions that make a difference. Don’t wait; dive right in!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"Strikes a nice balance of explaining fundamental data science concepts and theories, while also equipping readers with hands-on practice with Python. . . . definitely a good place to start data science."
—Ben Dickson, TechTalks

"Dive Into Data Science is a book every budding data analyst will want. Tuckfield covers the field with nuance and insight to show you what you can do and lead you to new ground. . . . If you have any interest in data science you’ll find this book a welcomed joy and refer to it for years to come."
—David S. Mazel, Principal/Manager Systems Engineer, Regulus-Group

"Another nice learning resource for newbie data scientists."
—Daniel D. Gutierrez, Editor-in-Chief, insideBIGDATA

"I highly recommend this book . . . The trick to writing an introductory Data Science book is to land on the right balance between 'now watch what this magical line of Python code does' and 'here’s what’s happening and what this approach is good for'. I think Dr. Tuckfield has done it."
—Dr. Daniel Zingaro, author of Algorithmic Thinking and Learn to Code by Solving Problems

"Dive Into Data Science is a concise, accessible guide that demystifies the essential tools and techniques used by data scientists, allowing anyone with a basic understanding of programming to explore and analyze data like a pro."
—Allen B. Downey, Staff Producer at Brilliant and author of Elements of Data Science and Modeling and Simulation in Python

"Comprehensive and thoroughly 'user friendly' in in organization and presentation, [Dive Into Data Science] is the ideal instructional reference guide to utilizing Python as a basic and essential part of doing business in today's increasing complex, competitive, and digital world . . . . a highly recommended addition to personal, professional, community, corporate, college, and university library Computer Programming & Business Management collections and supplemental MBA curriculum studies lists."
—Midwest Book ReviewBradford Tuckfield is a data scientist, a consultant, and a writer. He received a PhD from the Wharton School of the University of Pennsylvania, and a BS in Mathematics from Brigham Young University. He is the author of Dive Into Algorithms (No Starch Press) and Applied Unsupervised Learning with R (Packt). In addition to working as a data scientist and tech manager for top finance firms and startups, his research has appeared in academic journals spanning math, business management, and medicine.