Скачать или смотреть End-to-End Project: Customer Segmentation with RFM Analysis (Clustering Case Study)

Welcome to Gen AI Cafe! In this complete, end-to-end project, we build a powerful Customer Segmentation model from scratch. This is a classic, portfolio-worthy case study that shows how businesses use unsupervised learning and advanced feature engineering to understand their customers.

This is a masterclass in practical data science, taking you from raw transactional data to actionable business insights.

In this hands-on project, you will learn:
✅ Advanced Feature Engineering: The complete guide to RFM (Recency, Frequency, Monetary) analysis, a professional technique for creating meaningful customer behavior metrics from raw sales data.
✅ Finding the Optimal Number of Clusters: How to use the Elbow Method to determine the best number of segments for your customer base.
✅ Building the K-Means Model: The step-by-step process of implementing K-Means Clustering in Python using Scikit-learn.
✅ Interpreting Your Results: The most important step! We'll show you how to analyze your final clusters to define customer personas and drive real business strategy.

👋 I'm Sayan Dey, your host at Gen AI Cafe. With over 15 years of experience in enterprise AI and building LLM systems, I'm excited to guide you through the fascinating world of AI and Machine Learning.
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