Prerequisite : Machine Learning Foundations and Applications (AI42001) OR Machine Learning (CS60050)
Taught by : Adway Mitra, Plaban Kumar Bhowmik
Teaching Assistents :
Suraj Meshram, Sumanta Mishra
The course will cover several learning paradigms, covering 2 or 3 example algorithms of
each, to represent various approaches under each paradigm. We will provide several
example applications, primarily from computer vision but also from other domains. The
broad paradigms to be covered include:
1) semi-supervised learning
2) active learning
3) few-shot, one-shot and zero-shot learning
4) online learning
5) multi-task learning
6) meta-learning
7) transfer learning
8) adversarial learning
9) contrastive learning
10)explainable and interpretable learning