Lecture 5 (1 of 2) - Natural Language Processing: Embeddings and AI Agents

Professor Liew's YouTube lecture introduces natural language processing, focusing on the progression from representing sentences as tokens and embeddings. The discussion covers early techniques like bag of words and TF-IDF and their limitations, leading to the development of word embeddings like Word2Vec and their ability to capture semantic relationships in a dense vector space. The lecture further transitions to AI agents, outlining their core components such as memory and tools for interacting with their environment to achieve goals. Finally, the assignment encourages students to build an AI agent to assist with job searching, leveraging the concepts discussed.