We will also discuss the use of computational tools and methods for analyzing and processing natural language data, as well as how linguistic insights can be used to design better computational …

This course will provide you with a comprehensive understanding of the latest techniques, tools, and applications of LLMs so you can build applications or processes and further improve your …

The course will also explore more advanced topics such as sequential models, attention mechanisms, and large language models. Additionally, practical considerations for implementing NLP systems in …

This course will provide you with a comprehensive understanding of the latest techniques, tools, and applications of LLMs so you can build applications or processes and further improve your …

Prerequisites Basic knowledge of calculus, linear algebra, and probability Programming proficiency (no specific language required but Python is preferred) A machine learning course is recommended but …

This is a part of deep learning that is focused on Natural Language Processing (NLP) tasks. We will talk about various types of Language Models such as T5, GPT-3, Codex, Llama-2, Chincilla, and PaLM.

It will provide the basic background for students planning to do a thesis in this area. It will also be a self-contained course for anyone interested in natural language processing (e.g., including computer …

The course content will be delivered in a lecture format, with four assignments, a midterm, and a final exam. Graduate students must complete a project (optional for undergraduates).

Sep 19, 2024 · This course builds on the techniques and patterns learned in CS135 while making the transition to use an imperative language. It introduces the design and analysis of algorithms, the …

This course provides an introduction to Artificial Intelligence, covering some of the core topics that underlay automated reasoning.