Deploying ML Models with FastAPI and uv

A modern approach to serving ML models in production - Alexey Grigorev

Join us for a hands-on workshop on deploying machine learning models using FastAPI and uv, a modern Python package and virtual environment manager.

​Led by Alexey Grigorev, this live session introduces updated tools and workflows for building and serving ML models in production environments.

​By the end, you'll have a working web service exposing your model, packaged and ready for production.

​What You'll Learn

• ​How to structure your ML project for deployment
• ​How to manage environments and dependencies with uv
• ​How to build and expose your ML model using FastAPI
• ​How FastAPI compares to Flask for serving models
• ​How to containerize your service and prepare it for deployment

​It will be a live demo with practical tips and a chance to ask your questions. This workshop gives you a real feel for how ML models are deployed in real-world environments.
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​Thinking About ML Zoomcamp?
​This workshop offers a sneak peek into the type of projects and skills you'll build during the ML Zoomcamp, our free 4-month course that takes you from beginner to advanced ML engineer. It covers the fundamentals of ML, from regression and classification to deployment and deep learning.
​The new cohort of the ML Zoomcamp starts on September 15, 2025. You can join it by registering here.
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​About the Speaker

​Alexey Grigorev is the Founder of DataTalks.Club and creator of the Zoomcamp series.
​Alexey is a seasoned software and ML engineer with over 10 years in engineering and 6+ years in machine learning. He has deployed large-scale ML systems at companies like OLX Group and Simplaex, authored several technical books including Machine Learning Bookcamp, and is a Kaggle Master with a 1st place finish in the NIPS'17 Criteo Challenge.
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**Join our slack: https://datatalks.club/slack.html**