Instructor:
Muhammad Abu Bakar Siddique
585
Credits:
3.0
001
Building:
Whitehall Classroom Bldg
Room:
Rm.339
Semester:
Spring 2023
Start Date:
End Date:
Name:
Interm Top Cs: Nat Lang Proc W Deep Netw
Requisites:
Prereq: Restricted to computer science & electrical engineering majors. Others by permission.
Class Type:
LEC
3:00 pm
4:15 pm
Days:
MW
Note:
Natural Language Processing with Deep Neural Networks Natural Language Processing (NLP) has become one of the most important technologies of the modern age. Applications of NLP are everywhere because people communicate almost everything in natural language data. It is the branch of artificial intelligence that enables computers to understand, process, and generate natural language. In recent years, deep neural networks have yielded results that were unimaginable only a few years ago on a wide range of demanding real-world NLP tasks. This course introduces students to cutting-edge research in NLP using deep learning. It will begin by introducing deep neural networks, and then demonstrate how they are applied to build NLP systems such as machine translation, summarization, conversational systems, question answering, stylized text generation, fake news detection, and information extraction. We will not only explore how to use high-level NLP libraries (e.g., Hugging Face) but also examine Lego-like building blocks of the pre-trained language models, such as Transformers, BERT, GPT-3.
Topics to be selected by staff. May be repeated to a maximum of six credits, but only three credits may be earned by a student under the same topic.
Topics to be selected by staff. May be repeated to a maximum of six credits, but only three credits may be earned by a student under the same topic.
CS