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🟢 15 Most Important LeetCode Patterns​

Having solved over 1500 LeetCode problems, the author highlights that success on LeetCode is not about the number of problems solved but the patterns learned. Understanding key patterns helps identify solutions quickly, even for unseen problems.

Details

URL: 🔗 15 Most Important LeetCode Patterns

Published: 2024-11-24

Authors: Ashish

Tags:
leetcode, patterns, interview-prep, problem-solving, algorithms

Key Points​

  • Emphasis on patterns: Patterns like Two Pointers, Sliding Window, and Dynamic Programming simplify problem-solving.
  • Practical examples: Includes problems for hands-on practice with each pattern.
  • Efficiency tips: Focus on understanding when and how to use each pattern, not just solving problems blindly.

Summary of Contents​

Additional Resources​

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🟢 How I Mastered Data Structures and Algorithms​

This article outlines a practical roadmap to mastering Data Structures and Algorithms (DSA), sharing tips and strategies that helped the author secure positions at Amazon, Google, and Microsoft. From choosing the right learning order to optimizing revision strategies, the article emphasizes efficiency and reducing overwhelm.

Details

URL: 🔗 How I Mastered Data Structures and Algorithms

Published: 2024-11-24

Authors: Ashish

Tags:
data-structures, algorithms, leetcode, interview-prep, problem-solving

Key Points​

  • Focus on core topics first: Linear data structures like arrays and linked lists, followed by trees, heaps, and graphs.
  • Effective learning order: Start with basics, explore real-world applications, implement from scratch, and practice simple problems.
  • Reinforce knowledge with patterns: Recognize and apply common problem-solving techniques across problems.
  • Revision is key: Revisit previously solved problems to retain knowledge and tackle harder challenges incrementally.

Summary of Contents​

  • Three Pillars of DSA: Data Structures, Algorithms, and Problem-Solving Techniques form the foundation of learning.
  • Learning Strategy: Tackle topics one at a time, starting with basics and progressing systematically to advanced concepts.
  • Key Resources: Highlights courses, YouTube playlists, and GitHub repositories for mastering DSA.
  • Problem-Solving Patterns: Learn and apply patterns like Divide and Conquer, Dynamic Programming, and Sliding Window.
  • Retention Strategies: Regularly revisit and practice challenging problems to build long-term understanding.

Additional Resources​

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🔵 Master Graph Algorithms for Coding Interviews​

This article simplifies graph algorithms by focusing on the 10 most common patterns seen in coding interviews. It explains how each algorithm works, when to use it, and how to implement it, with relevant LeetCode problems for practice.

Details

URL: 🔗 Master Graph Algorithms for Coding Interviews

Published: 2024-11-24

Authors: Ashish

Tags:
graph-algorithms, interview-prep, leetcode, coding-interviews, problem-solving

Key Points​

  • Covers fundamental algorithms: DFS, BFS, Topological Sort, Union-Find, and more.
  • Implementation strategies: Includes both recursive and iterative approaches with time/space complexity analysis.
  • Practice problems: Links to LeetCode problems for hands-on learning.
  • Real-world applications: Shows where each algorithm is commonly used, like shortest paths and detecting cycles.

Summary of Contents​

  • Depth First Search (DFS): Traverses graphs by exploring as far as possible along each branch before backtracking.
  • Breadth First Search (BFS): Explores graph level-by-level, useful for shortest path in unweighted graphs.
  • Union-Find: Manages disjoint sets efficiently for applications like cycle detection and MST construction.
  • Shortest Path Algorithms: Covers Dijkstra, Bellman-Ford, and A* for finding optimal paths in weighted graphs.
  • Minimum Spanning Trees (MST): Explains Kruskal’s and Prim’s algorithms for constructing MSTs.

Additional Resources​

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🔵 20 Patterns to Master Dynamic Programming​

This article introduces 20 essential patterns that make Dynamic Programming (DP) more approachable and efficient for solving a variety of problems. It outlines when to use each pattern and provides direct links to LeetCode problems for practice, arranged from easy to hard. These patterns demystify DP by showcasing how recurring strategies can simplify complex problem-solving.

Details

URL: 🔗 20 Patterns to Master Dynamic Programming

Published: 2024-11-24

Authors: Ashish

Tags:
dynamic-programming, interview-prep, leetcode, problem-solving, algorithms

Key Points​

  • Introduces 20 core DP patterns to simplify learning and problem-solving.
  • Covers patterns like Fibonacci, Knapsack, Kadane’s Algorithm, and more.
  • Links to relevant LeetCode problems for hands-on practice.
  • Provides a structured approach, from beginner-friendly to advanced topics.

Summary of Contents​

  • Fibonacci Sequence Pattern: Focuses on problems with solutions dependent on smaller subproblems (e.g., Climbing Stairs).
  • Kadane's Algorithm: Optimizes contiguous subarray problems like Maximum Subarray Sum.
  • Knapsack Patterns: Includes both 0/1 and Unbounded Knapsack for resource allocation problems.
  • LCS and LIS Patterns: Solves sequence alignment and increasing subsequence problems.
  • Grid and Graph DP: Applies to pathfinding and optimization in 2D arrays and graph structures.
  • Advanced Topics: Bitmasking, State Machine, and Digit DP for handling specialized scenarios.

Additional Resources​

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