Dive Into Data Science

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.

"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"I highly recommend this book as your introduction to Data Science. You’ll use the most important Python data science packages, work with real data, and learn how to visualize and analyze data in ways that today’s data scientists do. 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, Associate Professor of Computer Science at UT Mississauga and author of Algorithmic Thinking and Learn to Code by Solving Problems

Bradford 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.