Dynamic Programming Playlist | Coding | Interview Questions | Tutorials | Algorithm

This playlist explains Dynamic Programming in a concise way. Explaining how to approach a Dynamic Programming problem and moreover how to identify it first.

Curated by: Aditya Verma (50 videos)

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Tracks in this Playlist

• Dynamic Programming | Introduction
• 2 Types of knapsack
• 3 01 Knapsack Recursive
• 4 01Knapsack Memoization
• 5 01 Knapsack Top Down DP
• 6 Identification of Knapsack Problems and Introduction
• 7 Subset Sum Problem
• Equal Sum Partition Problem
• 9 Count of Subsets Sum with a Given Sum
• 10 Minimum Subset Sum Difference
• 11 Count the number of subset with a given difference
• 12 Target sum
• 13 Unbounded Knapsack
• 14 Rod Cutting Problem
• 15 Coin change problem: Maximum number of ways
• 16 Coin change problem: Minimum number of coins
• 17 Coin change problem Contd.
• 18 Longest common subsequence Introduction
• 19 Longest common subsequence Recursive
• 20 Longest common subsequence Memoization
• 21 Longest common subsequence Top down DP
• 22 Longest Common Substring
• 23 Printing Longest common subsequence
• 24 Shortest Common SuperSequence
• 25 Minimum Number of Insertion and Deletion to convert String a to String b
• 26 Longest Palindromic Subsequence
• Private video
• 28 Minimum number of deletion in a string to make it a palindrome
• 29 Print shortest common Supersequence
• 30 Longest repeating subsequence
• 31 Sequence Pattern Matching
• 32 Minimum number of insertion in a string to make it a palindrome
• 33 Matrix chain multiplication Introduction Identification and General Format
• 34 Matrix Chain Multiplication Recursive
• 35 Matrix chain multiplication Memoization
• 36 Palindrome Partitioning Recursive
• 37 Palindrome Partitioning Memoization
• 38 Palindrome Partitioning Memoized Optimisation
• 39 Evaluate Expression to True Boolean Parenthesization Recursive
• 40 Evaluate Expression To True Boolean Parenthesization Memoized
• 41 Scrambled String Recursive
• 42 Scrambled String Memoized
• 43 Egg Dropping Problem Recursive
• 44 Egg Dropping Problem Memoization
• 45 Egg Dropping Problem Memoization Optimization
• 46 Dynamic programming on Trees Introduction and Identification
• 47 Dynamic Programming on Tree General Syntax
• 48 Diameter of a Binary Tree
• 49 Maximum Path Sum | From any node to any node
• 50 Maximum Path sum | From leaf node to leaf node