Notes
Math for ML
Mathematical foundations essential for Machine Learning including linear algebra, calculus, probability, and optimization.
These notes are being written. Each topic below becomes its own page as it is written. Contributions are welcome — every page is a Markdown file in the repository.
Planned topics
| Topic | Level | Tags |
|---|---|---|
| Linear Algebra ✅ | intermediate | vectors, matrices, eigenvalues, SVD |
| Calculus | intermediate | derivatives, gradients, optimization |
| Probability & Statistics | intermediate | probability, distributions, MLE, hypothesis testing |
| Optimization Techniques | advanced | convex optimization, gradient descent, SGD |
| Discrete Mathematics | intermediate | combinatorics, graph theory, networks |