Introduction to Algorithms and Machine LearningLinear AlgebraCalculusAlgebraBooklets

I write math books for fun as a way to consolidate and clarify my quantitative intuition. The goal is to provide deep intuition for the core concepts and connections, along with plenty of examples and exercises, while remaining as concise as possible.

A special thanks to Sanjana Kulkarni for her thoughtful suggestions and diligent proofreading of these books.

Print copies are available on Amazon for the minimum price possible (printing cost plus Amazon's fees).

Introduction to Algorithms and Machine Learning

(2022)   school program, pdf, print

Linear Algebra

(2019)   pdf, print


(2019)   pdf, print


(2018)   pdf, print


Below are some shorter manuscripts that I feel are interesting enough to share.

A Primer on Artificial Intelligence (2019)
What is AI; The First Wave: Reasoning as Search; The Second Wave: Expert Systems; The Third Wave: Computation Power and Neural Networks; Cutting Through the Hype.

Introduction to Python Programming (2019)
Getting Started in Colab; Strings, Ints, Floats, and Booleans; Lists, Dictionaries, and Arrays; If, While, and For; Functions.

Graphing Calculator Drawing Exercises (2019)
Intuiting Predictive Algorithms (2018)
Naive Bayes; MAP and MLE; Linear Regression; Support Vector Machines; Neural Networks; Decision Trees; Ensemble Models.

The Data Scientist's Guide to Topological Data Analysis (2017)
Connecting Calculus to the Real World (2017)
An Intuitive Primer on Calculus (2017)
Functions; Limits; Derivatives; Integrals; Sequences; Series.

The Physics Behind an Egg Drop: A Lively Story (2014)
Velocity; Momentum; Changes in Momentum; Force; Pressure; Troll Egg Drop.