## K means clustering

K means clustering explained using customer segmentation in R. Touches on Silhouette statistic, Calinski and Harabasz index and Elbow curve.

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# Tag: data analytics

## K means clustering

## Hypothesis test for population parameters

## All you ‘really’ need to know | Python Notebook | Advanced – Pandas

## Table of Contents

## Why are basics important?

## Time series EDA

## Multivariate Analysis

## Handling Google maps location data

## Univariate Analysis on in-time

and machine learning

K means clustering explained using customer segmentation in R. Touches on Silhouette statistic, Calinski and Harabasz index and Elbow curve.

Discussion on hypothesis testing. Introduction to z-test and t-test, Code for visualization of z-test and t-test.

It’s pretty obvious to summon the fact that you wouldn’t have clicked on this article if you have no understanding of the basics and intermediate level concepts of Python. You have? Then it is fair enough to go ahead with this article. You are confused with some basic stuffs, or perhaps forgot about it? IContinue reading All you ‘really’ need to know | Python Notebook | Advanced – Pandas

Links to all other posts in a structured way. Table of contents.

Explains why basics are important using a simple example.

Tutorial on Time Series EDA. Contains time plot, seasonal plots and correlogram plots (ACF) for in-time problem with reusable R code.

Tutorial on Multivariate analysis which is the second part of EDA. Explained using in-time problem with reusable R code.

Getting traffic, vehicle used, location and journey time from Google Maps. Integrating these factors for in-time problem.

Tutorial on Univariate analysis which is the first part of EDA. Explained using in-time problem with reusable R code.