With the increased availability of data from varied sources there has been increasing attention paid to the various data driven disciplines such as analytics and machine learning. In this course we intend to introduce some of the basic concepts of machine learning from a mathematically well motivated perspective.
We will cover the different learning paradigms and some of the more popular algorithms and architectures used in each of these paradigms.INTENDED AUDIENCE :
This is an elective course. Intended for senior UG/PG students.
BE/ME/MS/PhDPREREQUISITES :
We will assume that the students know programming for some of the assignments.If the students have done introductory courses on probability theory and linear algebra it would be helpful. We will review some of the basic topics in the first two weeks as well.INDUSTRY SUPPORT :
Any company in the data analytics/data science/big data domain would value this course.
