Overview
Learn about data mining concepts in this university lecture covering essential topics in text and image representations. Explore TF-IDF (Term Frequency-Inverse Document Frequency) techniques, dive into word embeddings and their applications in analogies, and examine important considerations regarding societal biases in language models. Gain insights into contextualized representations and their role in modern natural language processing, followed by an exploration of image representation techniques. The lecture begins with course logistics including policies, deadlines, and project requirements before delving into the technical content, making it particularly relevant for data science and machine learning students.
Syllabus
Recording starts
Policy
Deadlines
Project data collection
Schedule
Lecture motivation
TF-IDF
Word embeddings
Analogies
Societal biases
Contextualized representations
Image representations
Lecture ends
Taught by
UofU Data Science