A Philosophy of Software Design
Notes
Deep modules, complexity management. Best modern design book.
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Deep modules, complexity management. Best modern design book.
Epistemological anarchism. The strongest critique of scientific method.
Best practical stats-based ML introduction ever written.
Thermodynamics + statistical mechanics at the right level.
Practical patterns for designing internal and public APIs.
The standard AI textbook. Search, logic, planning, learning, language.
Bridge from computation to proof. Sets, logic, induction, functions.
Still the gentlest and most irreverent intro to calculus ever written.
The cleanest Newton → Lagrange → Hamilton pipeline.
How programs run on hardware. Assembly, linking, virtual memory.
Multiple drafts model of consciousness. Anti-qualia manifesto.
Introductory crypto for programmers. Accessible and practical.
Storage engines, B-trees, LSM-trees, distributed database internals.
The Gang of Four book. Know these patterns even to argue against them.
Comprehensive distributed systems textbook, free from the authors.
A full ODE treatment including BVPs and series methods.
The standard information theory textbook. Entropy, channels, coding.
Consciousness, self-reference, formal systems. Mind-altering.
Demystifying paradoxes from physics to ethics. LessWrong favorite.
The telephone book of general relativity. Exhaustive and beautiful.
Best modern probability textbook. Stat 110 at Harvard.
Automata, computability, complexity. The clearest treatment.
Deep truth about concurrency, memory models, and pain.
Clear, concept-first linear algebra without mysticism.
Russell’s quest for logical foundations, told as a graphic novel.
Unified LA + multivariate calc + probability for ML-minded people.
Bite-sized set theory for working mathematicians. Deceptively deep.
Visual, intuitive intro to neural nets. Build understanding from scratch.
VAEs, flows, diffusion, GPs, causal inference — the advanced sequel.
Comprehensive modern ML textbook with solid probabilistic foundations.
Quantum electrodynamics for non-physicists. Feynman at his clearest.
Conceptual nuclear weapon disguised as a book.
LessWrong sequences collected. Bayesian epistemology applied everywhere.
Minimal but profound introduction to ray/path tracing.
Curated classic database papers with commentary.
The RL bible. Bandits to policy gradients to planning.
Hypermedia, representations, profiles. REST done properly.
Special relativity made physical. Invariant interval first.
The canonical NLP book, updated for the LLM era.
Entropy, ensembles, and real statistical physics.
The modern Bayesian workflow explained with clarity and care.
Classical mechanics via computation. SICP meets Lagrangians.
What actually makes people good at predicting the future.
The Mount Everest of CS. Definitive but demanding.
How to do great work. Hamming’s lifetime of meta-level wisdom.
Rare events, fat tails, and the limits of prediction.
Affordances, signifiers, mental models. Applies to APIs and UIs alike.
The most famous physics lectures ever given. Free to read online.
Falsificationism as the demarcation of science. Foundational epistemology.
1000+ pages surveying all of modern mathematics. The map of math.
Soldier vs scout mindset. Practical applied rationality.
Paradigm shifts. Changed how we understand how science actually works.
Bayesian statistics by writing code. Ideal computational on-ramp.
Probability and statistics for programmers, learn by coding.
Modern DL explained cleanly without hype.