Course Description

Course Learning Objectives: This course (BCS714A) will enable students to:

● Understand the basic concepts of deep learning.

● Know the basic working model of Convolutional Neural Networks and RNN in decision making.

● Illustrate the strength and weaknesses of many popular deep learning approaches.

● Introduce major deep learning algorithms, the problem settings, and their applications to solve real world problems

 Course Outcomes: The student will be able to :

1. Interpret the concepts of neural networks learning processes.

2. Illustrate deep learning methods using regularization and Optimization process

3. Design deep learning models using convolutional operations.

4. Analyze sequential data to build recurrent and recursive models.

5. Demonstrate the different interactive applications of deep learning.

TEXT BOOKS

Text Book -1 : Ian Goodfellow, Yoshua Bengio and Aaron Courville, Deep Learning, MIT Press, 2016.

Text Book -2 :  John Krohn, Grant Beyleveld, Aglae Bassens, Deep Learning Illustrated, A Visual, Interactive Guide to Artificial Intelligence, Pearson, 2022.

E-REsources LINKS

https://sites.google.com/view/iukcoursewebsite/home   -- Course website 

https://www.coursera.org/learn/neural-networks-deep-learning --  Course Era

https://www.youtube.com/watch?v=VyWAvY2CF9c -- Deep Learning Crash course 

https://www.youtube.com/watch?v=7sB052Pz0sQ      -- Introduction to Deep Learning 

https://www.youtube.com/watch?v=Mubj_fqiAv8 –-  Deep Learning Tutorial 

https://onlinecourses.nptel.ac.in/noc20_cs62/preview   -- NPTEL Course