Pedro Tabacof is based in Dublin and is currently a staff machine learning scientist at Intercom. Previously, he has worked at Wildlife Studios (mobile gaming), Nubank (fintech), iFood (food delivery app). He has used and deployed machine learning models for anti-fraud, credit risk, lifetime value and marketing attribution, using XGBoost or LightGBM in almost all cases. Academically, he has a master's degree in deep learning and 300+ citations.
In this presentation, I will show how to use AWS Lambda and API Gateway to deploy real-time machine learning models developed in Python. I will use these tools to create a serverless web endpoint and serve model predictions with high availability/scalability. These tools provide a relatively simple and cost-effective solution for data scientists and machine learning engineers looking to deploy models without the hassle of managing servers and without needing to rely on third parties. I will cover potential pitfalls to be aware of, such as Lambda's cold start delays and memory limitations. Through code examples and practical tips, attendees will gain a solid understanding of how to use serverless AWS to deploy and serve their own machine learning models at scale.