Dynamic Programming: Introduction and Fibonacci Numbers

This lecture introduces Dynamic Programming as an algorithmic paradigm, focusing on the main idea of saving computation by remembering previous calculations. It covers the application of Dynamic Programming to solve optimization problems, with a specific example of calculating Fibonacci numbers efficiently. The lecture also discusses the top-down approach with memoization and its benefits in optimizing recursive algorithms. The content progresses to explain the process of cutting a rod to maximize profit using Dynamic Programming. The lecture concludes by highlighting the exponential inefficiency of a naive recursive approach.