A modular and scalable repository of essential math for Data Science, Machine Learning, and AI.
Built for consistency, revision, and clarity — across courses and beyond.
- Linear Algebra — vectors, matrices, eigenvalues, SVD
- Calculus — limits, derivatives, gradients, integrals
- Probability & Statistics — distributions, Bayes’ theorem, inference
- Optimization — cost functions, gradient descent, convexity
- Discrete Math — logic, sets, graphs
- Numerical Methods — approximation, iteration, stability
Each topic folder includes:
README.md→ Index of the reponotes.md→ Key concepts & formulasexamples.ipynb→ Python demosexercises.md→ Practice problems- Tagged by source (IITM BS or others) for traceability
- IITMBS Course: Course from IIT Madras in programming and data science degree.
- GFG Course: Coding and DSA practice course by GeeksforGeeks.
- Khan Academy: Online platform for learning mathematics.
- Ensure consistency across courses and future learning
- Enable quick revision before exams, interviews, or projects
- Link math fundamentals directly to ML applications
Open to ideas, tweaks, and improvements — fork, clone, or drop a PR!
Made with ❤️ by Naveen Garg
