Clustering is a machine learning technique used to group data points based on similarity. This guide is intended to walk you through the process of creating a clustering model to group your data. We'll be using a dataset of 1000 supermarket transactions from stores in Myanmar. The aim of our project is to group these transactions in order to find patterns in the buying habits of the supermarket's customers.

Correlation exposes the relationship between variables. We can use correlation to understand whether changing the values for variable A is likely to also change the values for variable B. This article explains how correlation works, the different types of correlation alongside pointing out how to measure degrees of correlation in Graphext.

This guide is intended to walk you through the process of analyzing customer reviews with Graphext. We will analyze a dataset of 42,656 reviews about 3 Disneyland branches.

This guide is intended to walk through the building of a market basket analysis project using Graphext. We will be working with a dataset of purchases made at a bakery in Edinburgh. The aim of the project will be to identify communities of products that are related to one another and to transform this information into useful business insights.

Tractor is a tool to scrape data from popular platforms. Use it to build datasets from information on Google, Twitter and Facebook Ads.