Model Finetuning for NLICovers the second assignment for the CS-552: Modern NLP course, focusing on transfer learning and data augmentation.
Variational Auto-Encoders and NVIBExplores Variational Auto-Encoders, Bayesian inference, attention-based latent spaces, and the effectiveness of Transformers in language processing.
Deep Learning for NLPIntroduces deep learning concepts for NLP, covering word embeddings, RNNs, and Transformers, emphasizing self-attention and multi-headed attention.
