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## Game Theory Concepts for Reinforcement Learning

There are many flavors of games in Game Theory which are interesting from Machine Learning perspectives, especially from multi-agent Reinforcement Learning applications. Here is the summary of multiple game types are if MinMax algorithm works and what type of strategy one needs to employ.

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## Information Theory Concepts for Machine Learning

Entropy is the fundamental unit of information in Information Theory and is extensively useful in Machine Learning. Let us introduce the concepts: Entropy, Joint Entropy, Mutual Information.

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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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## Binary Tree Traversal

A binary tree is one where each of its nodes has maximum two children nodes. These children are mostly known as Left and Right child. 1. In-order Traversal It goes from left child then current node then right childSo for the given tree above it will be: [2,17,7,19,3,100,25,36,1] 2. Pre-order Traversal It first deals with […]

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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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## Queue Data Structure

Discussion on the implementation of queue data structure

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## Freelance Machine Learning Project Proposal Template

This is the recommended template for a Project Proposal for a freelance Machine Learning project. This is my personal choice, and definitely depending on project requirements, you might need to explicitly modify change/modify/add to this list. One size does not always fit all for Machine Learning projects. But anyway this could be a good starting point.

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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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## Tips: Reading Hive Tables from Spark

Collection of useful tips when working with Big Data tools including Hadoop, Hive, Spark

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## Big Data Handy References

Integrating Apache Hive with Kafka, Spark, and BI: https://docs.cloudera.com/HDPDocuments/HDP3/HDP-3.1.5/integrating-hive/content/hive_hivewarehousesession_api_operations.html