Your First ML Model in Production: Examples and Considerations

Explore the journey of deploying a machine learning model into production in this 46-minute conference talk by Sabina Stanescu at the Toronto Machine Learning Series (TMLS). Learn how to align data science work with business objectives and organizational infrastructure. Discover methods for identifying impactful, executable data science projects and strategies for transitioning them to production environments. Gain insights into real-time and batch scoring techniques, and examine sample architectures for making model scores accessible through APIs or databases. Delve into processes and frameworks that facilitate iteration and testing throughout the model deployment lifecycle. Benefit from a real-world example that demonstrates the complete process, from initial data capture to real-time scoring in a production setting.