This repository serves as a personal reference and learning resource for mastering DP techniques such as memoization, tabulation, and space optimization.

Dynamic programming is a fundamental concept in algorithm design that is beneficial for solving problems with overlapping subproblems and optimizing substructures. This repository contains:

• Recursive approach
• Top-down (Recursive + Memoization) approach
• Bottom-up (Tabulation) approach
• Optimized versions with reduced space complexity (if possible)
• Clear comments and code organization for better understanding

• Fibonacci series
• Minimum cost of climbing stairs
• Minimum number of coins
• Maximum sum of non-adjacent elements in array or list
• Cut the rod into segment of length x, y, x.
• Count derangements
• Painting fence algorithm
• Knapsack problem
• Combination sum problem
• Perfect square
• Minimum cost for tickets
• Largest square area in matrix
• Minimum score triangulation of polygon
• Minimum sideways jumps
• Reducing dishes
• Longest increasing subsequence
• Maximum height by stacking cuboids
• Pizza with 3n slices
• Number of dice rolled with target sum
• Partition equal subset sums
• Minimum swaps to make sequence increasing
• Longest arithmetic sequence