Strategies for Optimizing Recursive Algorithms in Python

This analysis provides strategies, such as memoization, tail recursion, dynamic programming, and iteration, to optimize recursive algorithms in Python. It discusses the benefits and drawbacks of using memoization, provides code examples, and examines the implementation of a memoize decorator. The objective is to reduce time complexity and improve performance by caching results and avoiding duplicate computations.