Kei Nemoto
Kei currently works as a data scientist in the healthcare field. He uses his expertise in data science/software engineering to automate machine learning workflows at scale. He has a Master of Science in Data Science degree from the Graduate Center, City University of New York, where he extensively focused on deep learning for information retrieval. He is passionate about learning new technologies to achieve what was impossible yesterday.
Sessions
This talk is a gentle guide for MLOps engineers or data scientists who have basic knowledge of Docker to build a scalable machine learning service on Kubernetes and Knative (serverless technology). It also covers the challenge of setting up a model storage for Kubernetes and how Mlflow can be used to solve the problem.