Indian Institute of Information Technology, Allahabad
Computer Vision and Biometrics Lab (CVBL)
July-Dec 2022 Semester
Objective of the course: To get the students and researchers exposed to the state-of-the-art deep learning techniques, approaches and how to optimize their results to increase its efficiency and get some hands-on on the same to digest the important concepts.
Outcome of the course: As deep learning has demonstrated its tremendous ability to solve the learning and recognition problems related to the real world problems, the software industries have accepted it as an effective tool. As a result there is a paradigm shift of learning and recognition process. The students and researchers should acquire knowledge about this important area and must learn how to approach to a problem, whether to deal with deep learning solution or not. After undergoing this course they should be able to categorize which algorithm to use for solving which kind of problem. Students will be able to find out the ways to regularize the solution better and optimize it as per the problem requirement. Students will be exposed to the background mathematics involved in deep learning solutions. They will be able to deal with real time problems and problems being worked upon in industries. Taking this course will substantially improve their acceptability to the machine learning community – both as an intelligent software developer as well as a matured researcher.
- Class schedule
- Lecture: Thursday (CC3-5107, 11.00 am - 01.00 pm), Tute: Friday (CC3-5207, 11.00 am - 01.00 pm), Practice: Thursday (CC3-5422, 05.00 pm - 07.00 pm)
Schedule - Lectures
|L01-02||Linear Machines and Learning|
|L09||Deep Learning: Introduction, Motivation and Status|
|L10||Convolutional Neural Networks|
|L13-14||Loss Function and Regularization|
- C1 (30%)
- C2 (30%)
- C3 (40%)
- Computer Programming
- Data Structures and Algorithms
- Machine Learning
- Image and Video Processing
- Ability to deal with abstract mathematical concepts
Related Classes / Online Resources
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