Complete Interview Preparation

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- Tutorials
- Practice DS & Algo.
- Algorithms
- Analysis of Algorithms
- Asymptotic Analysis
- Worst, Average and Best Cases
- Asymptotic Notations
- Little o and little omega notations
- Lower and Upper Bound Theory
- Analysis of Loops
- Solving Recurrences
- Amortized Analysis
- What does 'Space Complexity' mean ?
- Pseudo-polynomial Algorithms
- Polynomial Time Approximation Scheme
- A Time Complexity Question

- Searching Algorithms
- Sorting Algorithms
- Graph Algorithms
- Pattern Searching
- Geometric Algorithms
- Mathematical
- Bitwise Algorithms
- Randomized Algorithms
- Greedy Algorithms
- Dynamic Programming
- Divide and Conquer
- Backtracking
- Branch and Bound
- All Algorithms

- Analysis of Algorithms
- Data Structures
- Interview Corner
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- Maths Notes (Class 8-12)
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- Maximum length subsequence with difference between adjacent elements as either 0 or 1 | Set 2
- Maximum difference between frequency of two elements such that element having greater frequency is also greater
- Difference between highest and least frequencies in an array
- Maximum difference between first and last indexes of an element in array
- Maximum possible difference of two subsets of an array
**Sorting using trivial hash function**- Smallest subarray with k distinct numbers
- Longest subarray not having more than K distinct elements
- Longest subarray with difference exactly K between any two distinct values
- Longest subarray in which absolute difference between any two element is not greater than X
- Longest subarray with absolute difference between elements less than or equal to K using Heaps
- Maximum length subarray with difference between adjacent elements as either 0 or 1
- Longest subarray such that the difference of max and min is at-most one
- Maximum absolute difference between sum of two contiguous sub-arrays
- Count pairs with given sum
- Given an array A[] and a number x, check for pair in A[] with sum as x (aka Two Sum)
- Majority Element
- Find the Number Occurring Odd Number of Times
- Largest Sum Contiguous Subarray
- Maximum Subarray Sum using Divide and Conquer algorithm
- Maximum Sum SubArray using Divide and Conquer | Set 2
- Sum of maximum of all subarrays | Divide and Conquer
- Internal Working of HashMap in Java
- Hashing | Set 1 (Introduction)
- Hashing | Set 3 (Open Addressing)
- Hashing | Set 2 (Separate Chaining)
- Sort string of characters
- Print Nodes in Top View of Binary Tree

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