Basics, Fun with Statistics, Python

Post-Hoc Analysis of ANOVA Test

Finding Relationship Between Variables – ANOVA (Part 2) Post-Hoc Analysis of ANOVA Test in Python This article is in continuation of my earlier post, Finding Relationship Between Variables – ANOVA Test. In that post, I have explained basics of ANOVA Test on when and how to implement it using Python programming language. We took the Auto MPG DataSet and tried to…

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Basics, Python

Using K-modes for clustering categorical data

Introduction to K-Modes Algorithm Clustering or (dividing into similar subgroups) forms a crucial part of data analysis.Dividing the entire data set into various similar subgroups helps us to gain a lot of insight from the data. All those who are in the field of analytics or trying to get into it must have heard about “K-means Algorithm”.It is one of the…

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Basics, Fun with Statistics, Python

Finding Relationship Between Variables – ANOVA Test

Finding Relationship Between Variables – ANOVA (Part 1) ANOVA Test in Python Finding the relationship between variables is a very important step in any statistical modeling. For example, you are working in a dataset which contains hundreds of variables but very few observations, you cannot simply include all those hundreds of variables in your modeling. Otherwise you will be violating…

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Basics, Python

Introduction to Linear Discriminant Analysis

Linear Discriminant Analysis Linear Discriminant Analysis or most commonly known as ‘LDA’ is one of the most interesting machine learning techniques till date.The idea was first coined by “Dr. Ronald Fisher” to classify binary classes using ‘Fisher’s linear discriminant‘ and later on it was generalized for multiple classes as well.In case of a binary class problem, LDA acts as a classifier like…

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Basics, Neural Networks, Python

Using K-means to find the optimal nodal center for Radial Basis Function

 Introduction In my previous article on “Introduction to the perceptron algorithm”  we had seen how a single layer perceptron model can be used to classify an OR gate. But when the same model was used to classify a XOR gate it failed miserably. The problem was with linearity, i.e. if the classes are not linearly separable “Single layer perceptron model”…

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Basics, Deep Learning, Neural Networks, Python

Introduction to the Perceptron Algorithm

Perceptron Algorithm The Perceptron model forms the basis of any neural network. This is where it all began and finally led to the development of “Neural Networks” or “Deep Learning” which is kind of the buzz word nowadays. In this article, I am going to show the mathematics behind the well-known Perceptron algorithm using a 2-input 2-output model. Although some amount of linear algebra…

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