This course aims to introduce the basic concepts of linear algebra, calculus and optimization with a focus towards the application area of machine learning and data science.
Manipulating matrices using matrix algebra.
Performing elementary row operations.
Using Gaussian Elimination: Solving systems of linear equations. Find out whether a set of vectors are linearly independent. Writing down a set of dependencies in case vectors are not linearly independent. Finding subspaces along with their bases and ranks.
Finding distances and angles using norms and inner products.
Obtaining orthonormal basis using the Gram-Schmidt process.
Finding maxima and minima of single variable functions using derivatives.
Finding maxima and minima of multivariate functions using vector calculus.
For details of standard term assessment timelines and exam structures, visit our Academics page.
I completed my B.Stat. (Hons.) and M.Stat. from the Indian Statistical Institute, Kolkata in 2004 and my Ph.D. from TIFR, Mumbai in 2010. I was a postdoctoral fellow in TIFR, a visiting assistant professor in the University of Kansas and very briefly an INSPIRE faculty fellow in IISc, Bengaluru before I joined the mathematics department in IITM in 2015.