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recommended books

I mean, I can't really recommend books to you since I don't really know who you are. But these are books I really adore. I almost exclusively read nonfiction, so there are not any fiction recommendations.

Science Popularizations

T-Rex and the Crater of Doom - Walter Alvarez

A compelling story that clearly lays out the combination of hard work and total luck that leads to big discoveries in science. So good!

The Immortal Life of Henrietta Lacks - Rebecca Skloot

Dives deep into ethics, race, poverty, medicine and medical research. Reads like investigative journalism, but more thoughtful. For months after reading this book, it was my go-to for conversations - I just had to tell everyone the story.

The Unwanted Sound of Everything We Want - Garret Keizer

This is a hard book to describe because it is so sprawling but also so personal. My favorite quote from the book captures the theme well: "The essential difference between music and noise is neither acoustic nor aesthetic but ethical."

Algorithms to Live By: The Computer Science of Human Decisions - Brian Christian, Tom Griffiths

This is the rare popularization that is accessible and interesting to a broad audience, but even folks I have talked to that study math or computer science learned interesting things from it.

Sun in a Bottle: The Strange History of Fusion and the Science of Wishful Thinking - Charles Seife

Learning about the history of fusion research was neat, but my favorite aspect of the book was seeing how many different ways scientists have failed at cold fusion. I liked the books above better, but this is a good runner up.

Data Science

There are lots of good textbooks on specific problems related to data science, but these are my favorites because the cover the big, complicated, messy world in accessible ways. They are all accessible

Confident Data Skills: Master the Fundamentals of Working with Data and Supercharge Your Career - Kirill Eremenko

I can only recommend chapters 1-5, but those are the best description I have found of what I do as a data scientist all day. Easy read - no math and lots of emphasis on understanding problems, soft skills and process.

The Visual Display of Quantitative Information - Edward R. Tufte

This is the classic book in data visualization. Because the recommendations have been so widely adopted, it now reads as less revolutionary than it was. I still recommend borrowing a copy and flipping through it.

Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy - Cathy O'Neil

I can't say I agree with everything in this book, but I have read quite a few critiques of how data / automation / AI / algorithms / etc. are harming society, and this is the most thoughtful and timely.


Pattern Classification (2nd Edition) - Richard O. Duda, Peter E. Hart and D. G. Stork

You want to understand machine learning? There are lots of books right now about how to do machine learning, but this 20 year old book lays out the basics in a way that is easy to understand. The appendix has the most clear and straightforward overview of the linear algebra and probability that you need.

Understanding Digital Signal Processing - Richard G. Lyons

This is a practical guide to actually implementing digital signal processing. Covers tons of important topics that aren't taught in school, and the extremely practical approach really worked for me. I read the 2nd edition, but there is a third now.

Nonlinear Dynamics and Chaos - Steven H. Strogatz

I loved this math textbook. I wish every math text could be like this.

Div, Grad, Curl, and All That: An Informal Text on Vector Calculus - H. M. Schey

Extremely informal, but this really helped me make sense of vector calculus. It should be paired with a proper textbook, but if you are struggling with

Books that changed my life, but I read them as a teenager

Chaos: Making a New Science - James Gleick

I read this book in undergrad, and it was thrilling to learn about the background of the things I was studying. It helped me seperate the concepts of uncertainty and randomness, and I think often of the 1-2-3 punch of the Heisenberg's uncertainty principle, Gödel's incompleteness theorems, and chaos in deterministic systems. I think in some ways data science is as much a response to those discoveries of the 20th century as they are to the rise in computers.

Nonzero: The Logic of Human Destiny - Robert Wright

Almost all interactions are not zero sum. Some of them are mutually beneficial, and others are mutually harmful. I think about this every day, despite reading this book roughly 20 years ago. I feel really badly for (and often am afraid of) people who see the world as zero sum.


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