Learn how to generate all permutations of a string using backtracking. This step-by-step guide with examples, diagrams, and Python code demonstrates backtracking string combinations for beginners to advanced learners.
Master the Longest Common Subsequence (LCS) problem with dynamic programming. Learn step-by-step explanation, examples, visual DP table illustrations, and optimized solutions for coding interviews.
Learn the Edit Distance (Levenshtein Distance) algorithm with a detailed step-by-step guide, Python implementation, time complexity analysis, and real-world use cases.
Master the Coin Change Problem using Dynamic Programming. Learn how to compute the minimum number of coins for a given amount with detailed examples, diagrams, Python code, and explanations.
Learn the Maximum Subarray Product problem using Modified Kadane’s Algorithm. Step-by-step explanation, visual diagrams, and Python code examples with outputs included.
Learn Palindrome Partitioning using Dynamic Programming. A complete guide with explanations, Python implementation, visual aids, and examples to understand this important string problem.
Learn everything about Matrix Chain Multiplication and the Optimal Parenthesization Problem with step-by-step explanations, visual diagrams, and dynamic programming examples.
Learn the O(n log n) Dynamic Programming solution for Longest Increasing Subsequence with clear explanations, examples, Python code, and visual diagrams.
Learn about Greedy Algorithms, their working principle of making locally optimal choices, and see practical examples like coin change, activity selection, and Huffman coding explained with visuals and code.
Explore the Activity Selection Problem with the classic greedy algorithm approach. Learn using detailed examples, visual explanations, and interactive diagrams.
