Natural Language Processing with Deep Learning

3 credits · Graduate

Natural Language Processing (NLP) is a field of Artificial Intelligence that enables computers to understand human language. It targets various applications such as, dialog systems like Amazon Echo, translation systems like Google translate, and text generation like auto-completion feature while writing emails and chatGPT. Neural network based approaches, particularly deep learning, have substantially improved the performance across various NLP tasks and have become the most common approach to solve NLP problems. This course aims at providing students with an in-depth knowledge of solving various NLP problems with deep learning. It begins with providing an introduction to neural network models and advances to the latest neural network architectures such as RNNs and Transformers. The students get an opportunity to see the application of deep learning models across major NLP problems and familiarize themselves with peculiarities involving text processing. Moreover, the course will introduce students to major recent advances in NLP. CALENDAR NOTES: Students must have taken a course covering classical machine learning topics such as classification, clustering, optimization in their undergraduate studies or the current graduate studies. EXCLUSIONS: CSCI 4158