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 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.