Antilibrary

Table of contents

Intro

Here is part of my antilibrary.

I haven't read anywhere near all of these books. Instead, this list is a way for me to keep track of good books I've found, and to pick the next book that I'd like to put at the top of my reading list (which is constantly reordered by whatever topic I'm interested in the most).

Remember: when reading a book, the best way to learn and remember what you've read is to actively engage with the book, e.g. by doing the exercises in the book, or by writing down questions at every stage of the reading — whether skimming or reading deeply — and then trying to answer those questions after reading, in your own words.

Software development and engineering

Process

Architecture

Programming

Systems thinking and design thinking

Problem analysis, decision analysis and decision making

  • How to solve it (Polya)
    • Heuristics for solving mathematical and other problems
  • How to measure anything (Hubbard)
    • Focuses on application, especially in business. Decision analysis, Bayesian probability, Monte Carlo methods.
  • Thinking and deciding (Baron)
    • More theoretical than How to measure anything
  • Scenario planning

Mental models

  • Super thinking (Weinberg)

Business

  • The unwritten laws of engineering (Skakoon)
    • Originally published in 1944
    • Also published as "The unwritten laws of business"
  • The Goal (Goldratt)
  • The E-Myth Revisited
  • Peopleware
  • The five dysfunctions of a team
  • Enterprise architecture as strategy
  • Accounts Demystified (Rice)
  • The Personal MBA (Kaufman)
  • Toyota Kata

Biographies, history, and other non-fiction

  • Boyd (Coram)
  • Letters from a Stoic (Seneca)
  • Discourses and Selected Writings (Epictetus)
  • A bridge too far (Ryan)
  • Sapiens (Harari)
  • A Little History of Economics (Kishtainy)
  • Economic Facts and Fallacies (Sowell)

Mathematics

  • Statistics measures the quality of information.
  • Optimization finds the best alternative.
  • Probability quantifies and manages uncertainty.
  • Control automates decision making.
  • Modeling and computation build the mathematical abstraction of reality upon which these and many other powerful mathematical tools operate.

Mathematics is indeed the foundation of modern decision making.

[source]

Note: you'll want to make sure math books contain solutions to exercises. Consistently trying to solve exercises is very important for learning.

General

Precalculus, Algebra

Modeling and operations research

Graph theory

Statistics and probability

Probability is a prerequisite for statistics.

Calculus is a prerequisite for advanced probability, but the basics of probability don't require calculus.

Information theory

Discrete math

Algorithms

Linear algebra

Calculus

Game theory

Category theory

Machine learning and data analysis

Exercises and tests