K-Means clustering is a popular unsupervised machine learning algorithm that is commonly used in the exploratory data analysis phase of a project. It groups data together into clusters based on similarities within the data. In this tutorial, we will go through the basics of running a k-means algorithm on well log data.
Timestamps:
0:00 Introduction
0:53 K-Means Clustering Theory
2:56 Jupyter Notebook Loading Data & Importing Libraries
5:53 Applying a Standard Scaler
8:27 Identifying Optimum Number of Clusters - Elbow Plot
11:20 Appling K-Means Clustering Algorithm
12:55 Plotting K-Means Clustering Results on a Scatter Plot
14:25 Comparing Results from Multiple K Values
18:40 Other Clustering Methods & Outro
DOWNLOAD NOTEBOOK & DATA
Data and notebooks for my entire YouTube series can now be found here:
https://github.com/andymcdgeo/Andys_YouTube_Notebooks
