Rustem Feyzkhanov, Machine Learning Engineer at Instrumental, presents the “Scaling Machine Learning with Containers: Lessons Learned” tutorial at the May 2025 Embedded Vision Summit.
In the dynamic world of machine learning, efficiently scaling solutions from research to production is crucial. In this presentation, Feyzkhanov explores the nuances of scaling machine learning pipelines, emphasizing the role of containerization in improving reproducibility, portability and scalability. Key topics include building efficient training pipelines, monitoring models in production and optimizing costs while handling peak loads.
You’ll learn practical strategies for bridging the gap between research and production, ensuring consistent performance and rapid iteration cycles. Tailored for professionals, this presentation delivers actionable insights to enhance the scalability and robustness of ML systems across diverse applications.
See here for a PDF of the slides.
