Serving ML Models at Scale with Seldon and Kubeflow
Open source machine learning tools to manipulate and store big data and apply complex algorithms to this data have matured greatly in recent years. However, the final step in any successful machine …
| Talk Title | Serving ML Models at Scale with Seldon and Kubeflow |
| Speakers | Clive Cox (CTO, Seldon) |
| Conference | KubeCon + CloudNativeCon Europe |
| Conf Tag | |
| Location | Copenhagen, Denmark |
| Date | Apr 30-May 4, 2018 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Open source machine learning tools to manipulate and store “big” data and apply complex algorithms to this data have matured greatly in recent years. However, the final step in any successful machine learning project is to put the models into production with exposed APIs as well as monitor, scale and continuously update them. Kubernetes offers the ideal platform to build an ML deployment platform. This talk will review some of the challenges in deploying machine learning models and discuss Kubernetes focused open source projects (Seldon Core, KubeFlow) that provide solutions.
