In this course, I’ll show you how to build a scalable, real-time fraud detection 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 Kafka, Spark, and modern ML workflows.
FULL VIDEO: https://youtu.be/BY26sqZLi3k
? What’s Inside:
✅ End-to-End Architecture (High-throughput Kafka clusters, real-time inference with Spark)
✅ ML Model Development (Feature engineering, training, and production promotion)
✅ Best Practices (Model retraining, performance optimisation, system scaling)
✅ Hands-On Walkthrough (Financial transaction simulation, fraud analysis, and results review)
Timestamps:
0:00 Introduction
4:08 High Level Architecture Walkthrough
17:46 System Requirements
22:40 Tools used and why
24:29 Machine Learning Features Walkthrough
30:00 Setting up the Architecture
1:00:00 Financial Transactions Producer
1:49:48 Creating High Throughput and High Performance Kafka Cluster
2:04:20 Training Fraud Detection Model
2:43:59 Machine Learning Features Implementation
4:21:00 Reviewing Generated Model and Promoting them to Production
4:44:00 Realtime Inference with Apache Spark
5:48:33 Review Fraud Transactions Inference Results
5:54:20 Outro
? Resources
Full Source Code: https://buymeacoffee.com/yusuf.ganiyu/full-source-code-building-end-end-fraud-detection-solution-scratch
For Youtube Members (Full source code available in the community): youtube.com/@CodeWithYu/community
? Tags:
fraud detection, machine learning, apache kafka, apache spark, data engineering, mlops, realtime analytics, cybersecurity, data pipeline, model deployment
? Hashtags:
#DataEngineering, #MachineLearning, #FraudDetection, #Kafka, #ApacheSpark, #TechTutorial, #MLOps, #CyberSecurity