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## LeetCode#34: Find First and Last Position of Element in Sorted Array

This LeetCode problem is a great practice problem to implement a binary search for a value in a sorted array with duplicate values. It asks to find the indices of the first and start the occurrence of a value in the sorted array with possibly duplicate values. It can be solved in a naive manner […]

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## LeetCode#75: Sort Color using Three-way Partitioning

The Sort Color problem expects to sort the array with values {0, 1, 2}. This can be done in a typical sorting algorithm in O(nlogn) time. A better approach is to use three-way partitioning of the array. Generic three-way partitioning Below the threeWayPartitionSort() method splits the given an array, [3,2,0,2,1,1,0,-1], into three parts, where values […]

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## Understanding Quick Sort and QuickSelect using Hoare Partition

This class implements a QuickSort algorithm using Hoare Paritioning scheme. This partitionining scheme is slightly harder to implement but is more efficient than the Lamuto partitioning scheme as it does three times fewer swaps on average [Wikipedia]. Avg Time-Complexity: O(nlogn) Worst Time-Complexity: O(n^2) Space complexity: O(1) Understanding Hoare Partition Intuitively After spending quite some on […]

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## LeetCode#94: Binary Tree Inorder Traversal

First check out the problem description here on LeetCode. The Solution This is marked as a medium difficult problem. However if you know what in-order traversal does, it is a very simple problem. Here I just added a helper traverse() method. All the trick is done in the few lines inside the function. It checks […]

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## Policy Iteration, Value Iteration, and Q-Learning

Quick introduction to basic Reinforcement Learning algorithms including Bellman Equation, Policy Iteration, Value Iteration, and Q-Learning

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## How To Compute Reconstruction Error for Random Projection

Random Projection is an interesting Dimensionality Reduction technique. You may choose to create a random projection for 1,2,3,..,n dimensional projections. Now how to tell which one is best? So you would need to calculate loss of data due to this reduction in data size. # data has this shape: row, col = 4898, 11 random_projection […]