The Dynamic Programming Manual: Mastering Efficient Solutions

Table of Contents
Preface: Unleash the Power of Dynamic Programming
Part I: Theory
	What is Dynamic Programming?
	Fundamental Concepts
	Advanced Dynamic Programming Techniques
	Dynamic Programming in Practice
	Advanced Topics in Dynamic Programming
	Tips and Tricks for Efficient Dynamic Programming
	Conclusion and Future Directions
Part II: Dive into Dynamic Programming Challenges
	Fibonacci Sequence
	Fibonacci with Memoization
	Last Digit of Fibonacci Number
	Longest Subsequence with Equal Elements
	Longest Subarray with Equal 0s and 1s
	Longest Common Subsequence
	Minimum Subset Sum Difference
	Valid Parentheses
	Minimum Number of Parentheses
	Find the Element that Appears Once
	Find the Missing Number
	Count Set Bits (Brian Kernighan's Algorithm)
	Generate All Subsets
	Power of Two
	Scalar Multiplication Order
	Topological Sorting
	Breadth-First Search (BFS)
	Depth-First Search (DFS)
	Symmetric Tree
	Lowest Common Ancestor
	Trim a Binary Search Tree
	Find Closest Value in BST
	Binary Tree Level Order Traversal
	Climbing Stairs
	Best Time to Buy and Sell Stock
	House Robber
	Coin Change
	Coin Change 2
	Knapsack Problem (Bottom-Up)
	0/1 Knapsack
	Knapsack with Duplicate Items
	Floyd-Warshall Algorithm
	Hamiltonian Path and Circuit
	N-Queens Problem
	Sudoku Solver
	Recover Binary Search Tree
	Edit Distance
	Dungeon Game
	Cherry Pickup
	Travelling Salesman Problem
Part III: Appendix
	Proof of Optimal Substructure Property
	Derivation of Memoization and Tabulation Techniques
	Problem Analysis
	Selecting the Right Data Structures for Dynamic Programming Efficiency