Hands On Data Science Project: Understand Customers with KMeans Clustering in Python

Try CodeCrafters for free using my referral link: https://app.codecrafters.io/join?via=... In this walkthrough, we dive into using data science to improve understanding customers by using KMeans clustering to classify online retail customers. Leveraging powerful libraries like sklearn and pandas, we'll walk through the entire process of analyzing customer data to uncover meaningful patterns and segments. You will learn how to: Import and preprocess customer data using pandas. Apply KMeans clustering to identify unique customer clusters. Visualize the clustering results to gain insights into customer behavior. Interpret the outcomes to drive improvement in customer experience. Whether you're a beginner looking to expand your data science skills or an experienced analyst wanting to refresh your knowledge, this tutorial provides a comprehensive guide to KMeans clustering in Python. Don't forget to like, subscribe, and hit the notification bell for more data science, data engineering and data analysis content! #DataScience #KMeans #Clustering #Pandas #Sklearn #Python #CustomerSegmentation #OnlineRetail #DataAnalysis 📖CHAPTERS 00:00:00 - Intro 00:02:35 - Setup 00:05:27 - Exploratory Data Analysis 00:24:23 - Data Cleaning 00:33:20 - How Does KMeans Clustering Work? 00:37:55 - Feature Engineering 01:11:59 - KMeans Clustering 01:25:40 - Cluster Analysis 01:33:31 - Outlier Analysis 01:41:34 - Visualisation 01:46:27 - Outro and Thanks! 🔗LINKS Online Retail Dataset: https://archive.ics.uci.edu/dataset/5... Online Retail Mining Whitepaper: https://link.springer.com/article/10.... Github Link: https://github.com/trentpark8800/onli... 🖼️PICTURE CREDITS Urgency/Importance Matrix: https://rushcuttershealth.com.au/how-... 💵SUPPORT THE CHANNEL Become a channel member:    / @trentdoesmath   Direct, once off transfers: https://www.paypal.com/paypalme/trent...