Model serving and deployment is the last mile to success in any machine learning project. However building the entire MLOps workflow for serving is challenging. ML teams often end up with complex and inefficient solutions, using tools that are not designed for this problem. BentoML is the open source framework for model serving, offering a simple workflow towards high performance model serving. In this talk, we will explore the key challenges in building a modern ML model serving stack and how BentoML could help.
Chaoyu Yang is a core contributor to BentoML, the open source ML model serving framework. He is also the founder and CEO of BentoML.ai. Previously, Chaoyu was an early software engineer at Databricks, working on its Data Science and ML platform. Chaoyu is on twitter @chaoyu_.
