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In this course, I’ll show you how to build a scalable, Churn prediction system from scratch—perfect for developers, data scientists, and tech enthusiasts! Learn industry best practices for machine learning model creation, retraining, and deployment, while mastering tools like Apache Airflow, MLFlow, Streamlit and modern ML workflows. 🔍 What’s Inside: ✅ End-to-End Architecture ✅ ML Model Development (Feature engineering, training, and production promotion) ✅ Best Practices (Model retraining, performance optimisation, system scaling) ✅ Hands-On Walkthrough Timestamps: 0:00 Introduction 1:17 System Architecture 4:00 Prerequisites and Installations 7:23 ML Services Dependencies 19:35 Setting up Training Dags 57:51 ML Pipeline for Improved Optimised Tuning 1:45:10 Streamlit Inference and Results Validation 1:53:55 Outro 📚 Resources Full Source Code: https://buymeacoffee.com/yusuf.ganiyu/source-code-customer For Youtube Members (Full source code available in the community): youtube.com/@CodeWithYu/community 📌 Tags: churn prediction, machine learning, apache airflow, data engineering, mlops, realtime analytics, data pipeline, model deployment 🔥 Hashtags: #DataEngineering, #MachineLearning, #ChurnPrediction, #TechTutorial, #MLOps, #CyberSecurity
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