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An Intuitive Explanation of Naive Bayes Classifier

Introduction In this post, let’s take a look at the intuition behind Naive Bayes Classifier used in machine learning. Naive Bayes classifier is one of the basic algorithms often encountered in machine learning applications. If linear regression was based on concepts from linear algebra and calculus, naive Bayes classifier mostly backed up by probability theory. …

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Iterative Policy Evaluation

Iterative Policy Evaluation for Estimating Value Function

Introduction In this tutorial, I am going to code the iterative policy evaluation algotithm from the book “Reinforcement Learning: An Introduction by Andrew Barto and Richard S. Sutton”. I am going to take psuedo code, image and examples from this text. The example I am taking for this tutorial is the gird world maze from Chapter …

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discount factor dynamics

Discount Factor in Reinforcement Learning

This article shows two key visual intuitions behind the usage of a discount factor in reinforcement learning with image, code, and video. Introduction Most of the advances in science and technology happened in the last 100 years. We can see mind-boggling progress in automotive, medicine, communication, energy, etc. . Among these advances, some technologies shake …

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epsilong greedy algorithm rewards

Epsilon Greedy Algorithm in Bandit Problems

Introduction Bandit problems are the simplest possible reinforcement learning scenario. Here the bandit machine can have k arms and pulling each arm leaves the user a reward. One of the arms will be giving higher rewards in the long run and moreover this pattern could be changing over a time period. Think of the scenario …

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