minmax scaling

Visualizing MinMax Scaling

This article explains the minmax scaling operation using visual examples. Normalization of vectors, an array of values, signals is often used as a preprocessing step before many algorithms. For example, in machine learning, some types of algorithms are prone to different inherent scales of features. In such situations normalization is done to give the same …

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Normal distribution visual explanation

Gaussian Distribution Explained Visually

Gaussian distribution appears in various parts of science and engineering. Apart from a distribution often appear in nature, it has got important properties such as its relation to Central Limit Theorem (CLT). The figure above shows one-dimensional Gaussian distributions of various mean and variance values. Libraries like NumPy provide functions that can return Gaussian distribution …

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Coding a Simple Markov Decision Process

A Markov Decision Process (MDP) is a mathematical framework used to model decision-making situations where the outcome of a decision depends on both the current state of the system and the actions taken by the decision maker. In an MDP, the decision maker is represented as an agent, and the system is represented as a …

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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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linear regression

An Intuitive Explanation of Linear Regression

Linear regression is one of the algorithm machine learning enthusiasts start to learn first. In this article, l will walk you through the linear regression intuition. We will implement the basic form of it without using any machine learning packages. The main philosophy of supervised machine learning algorithms is to learn from data. The algorithms …

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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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