Build a Fraud Detection AI from Scratch - End to End Machine Learning Project - Part 1

Learn how to build a scalable, real-time fraud detection system from scratch in this comprehensive tutorial aimed at developers, data scientists, and tech enthusiasts. Master industry best practices for machine learning model creation, retraining, and deployment while working with powerful tools like Apache Kafka and Spark. The tutorial covers the complete end-to-end architecture including high-throughput Kafka clusters and real-time inference with Spark, ML model development with feature engineering and production promotion, and system optimization techniques. Follow along with the hands-on walkthrough that includes financial transaction simulation, fraud analysis, and results review. The content progresses from introduction and architecture overview through system setup, model training, implementation of machine learning features, and finally to real-time inference and results analysis.