Data Science Foundations

This lecture introduces the foundational concepts in data science, covering topics such as information theory, signal representation, and estimation theory. The instructor discusses the importance of understanding the theory behind algorithms, the connection between different topics in data science, and the challenges of navigating various techniques. The lecture explores the multi-arm bandits model, distribution estimation, and the optimization question related to exponential families. The goal is to help students grasp the connections between different pieces of data science and develop a deeper understanding of the field.