Learn to Code with Basketball by Nathan Braun (.PDF)
File Size: 10 MB
Learn to Code with Basketball: Learn Python, webscraping, Machine Learning and more, all applied to basketball data by Nathan Braun
Requirements: .PDF reader, 10 MB | True PDF
Overview: A hands-on, beginner-friendly guide to Python and Data Science — taught entirely through NBA data. What is Data? At a very high level, data is a collection of structured information. You might have data about anything, but let’s take a basketball game, say Lakers vs Clippers. What would a collection of structured information about it look like? Let’s start with collection, or “a bunch of stuff.” What is a basketball game a collection of? How about shots? This isn’t the only acceptable answer — a collection of players, teams, possessions, or quarters would fit — but it’ll work. A basketball game is a collection of shots. In this book, we will be working with Python, a free, open source programming language. This book is hands on, and you’ll need the ability to run Python 3 code and install packages. Spyder is free, open source program that lets you view, write and run Python code. It’s easy to set up and comes with most of what we need, although we’ll have to grab some extra packages once we get to chapter 6. It’s probably the best option for most people right now. All in the context of basketball, and designed so you can apply it to your own questions and do your own analysis.
Genre: Non-Fiction > Tech & Devices
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