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. My Medium article this video is based on. Check it out as it contains more examples and extra plots. 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: REFERENCES & LIBRARIES Force 2020 Competition Github: Bormann P., Aursand P., Dilib F., Dischington P., Manral S. 2020. FORCE Machine Learning Competition. Competition Results: Books I Recommend: As an Amazon Associate I earn from qualifying purchases. By buying through any of the links below I will earn commission at no extra cost to you. PYTHON FOR DATA ANALYSIS: Data Wrangling with Pandas, NumPy, and IPython UK: US: FUNDAMENTALS OF PETROPHYSICS UK: PETROPHYSICS: Theory and Practice of Measuring Reservoir Rock and Fluid Transport Properties UK: US: WELL LOGGING FOR EARTH SCIENTISTS UK: US: GEOLOGICAL INTERPRETATION OF WELL LOGS UK: US: If you haven't already, make sure you subscribe to the channel: ----- Thanks for watching, if you want to connect you can find me at the links below: Be sure to sign up for my newsletter to be kept updated when I post and share new content on YouTube and Medium. #petrophysics #python #MachineLearning #unsupervised-learning