Course Description

Deep learning added a huge boost to the rapidly developing fields of machine learning and computer vision. Computer vision as a field is concerned with the question of how to equip computers with the intellectual capability of seeing and interpreting the world. Computer vision traditionally, worked very good in problems that are relatively difficult for humans but got stuck in problems which are easier for humans but hard for them to describe. Deep learning with its ability to learn task specific representation from myriads of data has revolutionized the field like nothing else before. This subject aims to provide students with foundational concepts required for deep learning. On having studied this subject a student is expected to be able to build analytic solutions to problems in signal, image and video paradigm using deep neural networks. The course will require the students to complete a research level project using Deep Learning concepts which will result in a poster session at the end of the course. As a rapidly evolving subject, Deep Learning requires the practioners to be aware of the state-of-the-art. The course, thus, will require the students to read recent as well as classic papers on this subject and present them in the class. Students on completion are expected to be able to understand and apply the concepts of deep neural networks and will be able to develop solutions using it.

Instructor

Class Time and Location

Wednesday (11:00am-11:55am), Thursday (12:00-12:55pm) and Friday (8:00am-8:55am)
NR421, Nalanda Classroom Complex, Third Floor

Office Hours and Email

Abir Das (abir@cse.iitkgp.ac.in)
Buridi Aditya (buridiaditya@gmail.com)
Vishal Gupta (ervishal@iitkgp.ac.in )
C. Sree Theerdha (sreetheerdha9@gmail.com )
Vishesh Agarwal (vishesh0512@gmail.com )
Subrata Chattopadhyay (subrata.ctj@gmail.com )

Office: Takshashila Building (Second Floor)
Hours: Thursday 4:00pm-5:00pm

Have questions?

We welcome your questions about the course including lectures, assignments, projects, and logistics on Piazza. Email the TA or instructor about questions that specifically pertain to you as an individual.