Ashutosh Patidar
MS (by Research) in Data Science & AI, IIT Madras. Working on mechanistic interpretability of in-context learning in transformers. These are my study notes.
Revision
Probability and Statistics Revision
Revision notes on probability and statistics.
Linear Algebra (source: Gilbert Strang notes)
Lecture-by-lecture notes on MIT 18.06 Linear Algebra (Spring 2010, Prof. Gilbert Strang), read through an ML / DL / AI lens. The series opens with PCA from the IIT Madras MLT course, works through all 34 lectures in order, and closes with a condensed revision sheet.
Machine Learning Revision (source: Arun Rajkumar, DA5400)
Lecture-by-lecture revision notes for the DA5400 machine learning course: clustering and K-means, estimation (maximum likelihood, Bayesian, GMMs and EM), and regression (least squares, projections, gradient descent, kernels, the probabilistic view and cross-validation). Interactive demos on every page.
SQL for Data Science (source: Nitish Singh, CampusX)
Interactive chapter-by-chapter notes on CampusX's six-hour MySQL course: databases vs files, DBMS, keys, integrity, ER diagrams, DDL and DML queries, GROUP BY, CASE, joins and subqueries. Quizzes on every page and a live SQL engine in the browser.
Deep Learning Revision (source: Mitesh Khapra, CS6910)
Comprehensive revision notes from the lectures of the CS6910 Deep Learning course (IIT Madras).
Coming soon: revision notes on hot topics in industry, such as RAG (retrieval-augmented generation) and AI agents.