Creative Coding: the blueprint for signals and audio synthesis in Chapter 7.

Deep Learning: the blueprint for more advanced machine learning in Chapter 10.

Introduction to Data Science: the bluebrint for probability and Monte Carlo simulations in Chapter 4.

Linear Algebra: Foundations to Frontiers: the blueprint for matrices in Chapter 9.

The Nature of Code: a key inspiration for this project and the blueprint for vectors in Chapter 9.

OpenStax: a great collection of free textbooks referenced at the end of each chapter.

p5.js: a delightful JavaScript library for creative coding used throughout the book.

p5.js Web Editor: the code editor adapted for use with this book.

R for Data Science: the blueprint for the data science process in Chapter 5.

Skulpt: an implementation of Python that runs in the web browser.