Dynamic Programming: Rod Cutting and Change Making

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Dynamic Programming: How Many Ways to Make Change

Demonstrates dynamic programming to find the number of ways to make change using different coin denominations.

Coin Change Problem

Explores the coin change problem, comparing greedy and dynamic programming algorithms for optimal solutions.

Markov Decision Processes: Foundations of Reinforcement Learning

Covers Markov Decision Processes, their structure, and their role in reinforcement learning.

Controlled Stochastic Processes

Explores controlled stochastic processes, focusing on analysis, behavior, and optimization, using dynamic programming to solve real-world problems.

Dynamic Programming: Introduction and Fibonacci Numbers

Introduces Dynamic Programming, focusing on saving computation by remembering previous calculations and applying it to solve optimization problems efficiently.

Dynamic Programming: Fibonacci Numbers

Covers dynamic programming with a focus on Fibonacci numbers and the rod cutting problem.

Optimization with Constraints: KKT Conditions

Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.

Optimization Methods: Theory Discussion

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Dynamic Programming: Optimal Decision Making

Explores dynamic programming for optimizing decision-making processes over time, using real-world examples like oil extraction and stock trading.

Algorithm Design: Divide and Conquer

Covers recursion, dynamic programming, and algorithm design using divide and conquer strategies.