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- No specific reading linked yet. Check the main list above.
Resources to learn the specific branches of mathematics relevant to coding: Discrete Math, Linear Algebra, and Statistics.
Math isn't about memorizing formulas; it's about learning how to think logically. Linear Algebra is the engine of AI/ML. Discrete Math is the logic of database sets and algorithms.
Focus on intuition first (visualizing the concept), then the calculation. Use interactive tools rather than dry textbooks.
| Topic | Resource | Description |
|---|---|---|
| Linear Algebra | Immersive Math | The world's first fully interactive linear algebra textbook. Rotate the vectors, don't just stare at them. |
| Visualization | 3Blue1Brown (Essence of Linear Algebra) | YouTube series. If you watch one thing, watch this. It gives you the 'brain eye' for math. |
| Deep Dive | Khan Academy | The gold standard for structured practice. |
| AI-Engineering.academy | Applied AI Curriculum | Free applied AI curriculum covering ML math foundations. |
| fucking-algorithm | Algorithm Guide | Walkthroughs and patterns for LeetCode and algorithmic problem solving. |
| cs-video-courses | Video Course List | Curated list of CS courses with video lectures. |
| Resource | Type | Description |
|---|---|---|
| Project Euler | Challenges | Solves complex math problems using programming. |
| Metacademy | Knowledge Graph | Open source package manager for knowledge. Tells you exactly what prereqs you need for a specific ML topic. |
| Topic | Resource | Description |
|---|---|---|
| Discrete Math | MIT 6.042J (OCW) | Full MIT course with video lectures, notes, and problem sets. Free. |
| Discrete Math | Rosen – Discrete Math and Its Applications | The standard textbook for discrete structures in CS programs. |
| Linear Algebra | MIT 18.06 (OCW) | Strang's lectures. The other LA essential besides 3Blue1Brown. |
| Calculus | MIT 18.01 (OCW) | Single-variable calculus, Strang's textbook included as PDF. |
| Probability | Think Stats (Allen Downey) | Bayesian-flavored intro stats using Python; free PDF. |
| Probability | Think Bayes (Allen Downey) | Bayesian stats via Python; companion to Think Stats. |
| Statistics | OpenIntro Statistics | Open-access undergrad stats textbook, used at many universities. |
| Theory | Mathematics for Computer Science (Lehman) | Updated MIT OCW print with proofs. |
| Visualization | Better Explained | Acheive intuition first; each post ends with a "in plain English" summary. |
| Visualization | Wolfram MathWorld | Definitive encyclopedia-style math reference. |
| Visualization | Matrix Calculus (Wikipedia) | Compact derivation reference for ML backprop. |
| Reference | Proof Wiki | Crowd-sourced proof encyclopedia. |
| Resource | Type | Description |
|---|---|---|
| Mathigon | Interactive Textbook | Beautiful, puzzle-driven textbook for discrete math and probability. |
| Brilliant | Interactive Course | Bite-size problems across algebra, logic, probability. Free tier is enough. |
| Desmos | Graphing Calculator | Free browser graphing tool; good for visualizing functions and trig. |
| GeoGebra | Dynamic Geometry | Interactive geometry, algebra, and calculus visualizations. |
| Wolfram Alpha | Computational Engine | Symbolic math and step-by-step solutions. Free tier covers most use cases. |
| Computational Thinking (MIT) | Course | MIT OCW intro to algorithmic and mathematical reasoning. |
| Immersive Linear Algebra | Interactive Textbook | Rotate, project, and scale vectors right in the browser. |
| 3Blue1Brown: Essence of Calculus | Video Series | Builds geometric intuition for derivatives and integrals. |
| Cut-the-Knot | Problem Archive | Hundreds of worked geometry, probability, and logic problems. |
| Topic | Resource | Description |
|---|---|---|
| Numerical Methods | Numerical Recipes (Press et al.) | Free online version of the classic algorithms book. |
| Optimization | Convex Optimization (Boyd & Vandenberghe) | Free Stanford textbook; foundation for ML optimization. |
| Information Theory | Information Theory, Inference, and Learning Algorithms (MacKay) | Free PDF; canonical reference for cross-entropy, KL, channel capacity. |
| Number Theory | Concrete Mathematics (Graham, Knuth, Patashnik) | CS-flavored math reference — recurrences, sums, combinatorics. |
| Logic & Proofs | How to Prove It (Velleman) | Friendly intro to mathematical proof technique. |
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