Prerequisite : Machine Learning
Taught by : Jiaul Paik, Somdyuti Paul, Mahesh Mohan
Teaching Assistents :
Anjali Raj, Priyanka, Raviteja Sista, Ashraf Rashid, Suvvada Rishi, Saurabh Mishra, Leo Lorence
Foundational concepts of linear algebra, probability, neural networks and learning theory
Software toolkits and deep learning libraries
Convolutional and recurrent neural networks
Regularization and learning concepts
Basics of dataset handling for deep learning
Numerical precision of deep learning computation
Quantifying perception losses and Adversarial learning
Federated deep learning
Deep learning for machine translations and text summarization
Building chatbots with cognitive capability
Deep learning for image classification, scene understanding
Semantic segmentation and single shot multibox detection
Medical image classification, compression and super resolution