Welcome 👋
This repository is a living notebook where I organize my understanding of core Computer Science and Data Science concepts—built while studying, revising, and questioning why things work the way they do.
I am still in the process of adding more things to this. These notes are intended for GATE aspirants and anyone currently pursuing the IIT Madras BS in Data Science and Applications Degree. Reach out to me at sly.of.zero@gmail.com if you want to collaborate in this alongside me! Cheers 🍻!
Rather than being a dump of formulas, these notes focus on:
- intuition before optimization
- derivations before results
- mistakes, edge cases, and “why not?”
How problems are solved.
Includes:
- divide & conquer, greedy, dynamic programming
- time and space complexity analysis
- recurrence relations and their solutions
- correctness arguments and trade-offs
📂 Start here → [[Algorithms]]
How data is organized.
Includes:
- linear and non-linear structures
- internal representations and memory layout
- operation costs and invariants
- when not to use a structure
📂 Start here → [[Data Structures]]
The language behind algorithms.
Includes:
- logic, sets, relations, and functions
- combinatorics and counting arguments
- recurrences, proofs, and asymptotic reasoning
- graphs, trees, and their properties
📂 Start here → [[Discrete Maths]]
“An algorithm is not just a procedure — it is a proof that a problem can be solved.”
These notes are continuously refined as my understanding improves.