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🪐 Leetcode DS & Algo Resources

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DSA_Problems_to_start_with_.pdf5.69 KB

Variations of DP: -Dynamic programming in one dimension -Dynamic programming over graphs and matrix -Dynamic programming with bit masks

Steps to start over DSA: 1. COMPLEXITY: How to analyze algorithms? Introduction to Big-O Notation? What is time complexity? What is space complexity ? Reverse engineering a solution Complexity Calculation: - Time Complexity Calculation - Standard Case Time Complexity Calculation - Iterative Case #l Time Complexity Calculation - Iterative Case #2 Time Complexity Calculation - Standard Case & Recursive Case Space Complexity Calculation - Standard Method Space Complexity Calculation - Recursion Tree Method Space Complexity Calculation - Back Substitution Method 2. ARRAYS Why are arrays fastest? -Understanding resizable arrays -Problems based on arrays -Two Pointer Approach -Moving pointers towards each other -Sliding Window Approach & Fixed Window Approach -Resizable Window 3.LINKED LISTS - Linked Lists And why we use them, implementation part -Linked List Standard Technique -Linked List Multi Pointer Technique - Linked List Implementation Techniques -Linked List Pointer Manip Technique + STACKS AND QUEUES 4. Search Algorithms: Binary Search & Linear Search Search Problems: -Standard Binary Search Technique - Modified Binary Search Technique - Binary Search Over Range Technique - Binary Search - Rotation Technique 5. TREES AND HEAPS General Trees & Binary Trees - Types of Binary Trees -Binary Tree - PostOrder Problems -Binary Tree - PreOrder Problems - Tree Construction Problems - Heaps & Heap Problems - BST Construction Problems 6. GRAPHS Graph Traversal - Shortest Path Problem Graph Problems: ~ Problems based on BFS - Problems based on DFS 0-1 BFS Problems based on backedge calculation Ad-hoc problems based on graph 7. GREEDY AND DP Greedy Algorithms - Greedy Algorithms & Applications Greedy + Data Structure Dynamic Programming

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