Discussion on memoization and tabulation techniques for solving Fibonacci problems. Common pitfalls and optimizations.
Exploring the differences and dynamic programming solutions for both variations of the Knapsack problem. Understanding constraints.
Detailed breakdown of the LCS DP approach. Applications in bioinformatics and text comparison. Implementation examples.
Strategies for finding the minimum number of coins to make a change. Handling edge cases and coin availability.
Understanding the optimal parenthesization for multiplying a chain of matrices using dynamic programming.
Discussing the DP solution for edit distance and its use in spell checkers and DNA sequencing.