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Top 5 Algorithms for Coding Interviews
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Here are the Top 5 Algorithms asked in coding interviews:
1️⃣ Top k Elements Algorithm: This algorithm is used to find the top k elements in an array based on a given criteria.
👉 Example Problem: Finding the k largest/smallest/most frequent numbers in an array.
2️⃣ Sliding Window Algorithm: Sliding window is a technique to efficiently process arrays or strings in a fixed-size window or substring.
👉 Example Problem: Finding the largest substring without repeating characters.
3️⃣ Backtracking: Backtracking is a recursive algorithm that explores all possible solutions by building them step by step and backtracks when an invalid state is encountered.
👉 Example Problem: Solving the Combination Sum problem, where you need to find unique combinations of numbers that add up to a target sum.
4️⃣ Dynamic Programming: Dynamic programming involves breaking down a problem into smaller subproblems and solving them to find the optimal solution.
👉 Example Problem: Solving the Combination Sum problem with dynamic programming by building solutions from smaller target sums.
5️⃣ Breadth First Search (BFS) and Depth First Search (DFS): BFS and DFS are graph traversal algorithms. DFS explores as far as possible along each branch before backtracking, while BFS explores neighboring vertices before deeper ones.
👉 Example Problem: BFS can be used to find the shortest path between two vertices in a graph, while DFS is commonly used for tasks like topological sorting
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1️⃣ Top k Elements Algorithm: This algorithm is used to find the top k elements in an array based on a given criteria.
👉 Example Problem: Finding the k largest/smallest/most frequent numbers in an array.
2️⃣ Sliding Window Algorithm: Sliding window is a technique to efficiently process arrays or strings in a fixed-size window or substring.
👉 Example Problem: Finding the largest substring without repeating characters.
3️⃣ Backtracking: Backtracking is a recursive algorithm that explores all possible solutions by building them step by step and backtracks when an invalid state is encountered.
👉 Example Problem: Solving the Combination Sum problem, where you need to find unique combinations of numbers that add up to a target sum.
4️⃣ Dynamic Programming: Dynamic programming involves breaking down a problem into smaller subproblems and solving them to find the optimal solution.
👉 Example Problem: Solving the Combination Sum problem with dynamic programming by building solutions from smaller target sums.
5️⃣ Breadth First Search (BFS) and Depth First Search (DFS): BFS and DFS are graph traversal algorithms. DFS explores as far as possible along each branch before backtracking, while BFS explores neighboring vertices before deeper ones.
👉 Example Problem: BFS can be used to find the shortest path between two vertices in a graph, while DFS is commonly used for tasks like topological sorting
.
❣️ Save for later and follow for more!
.
.
.
💻 Follow us on LinkedIn:
.
.
.
.
#programming #hacks #softwareengineer #technology #leetcode #codinginterview
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