On-Demand Webinar

Achieving MLOps with Kubeflow

Finding it difficult to maintain existing models? MLOps helps to deploy, monitor, and manage ML production with better accuracy and speedy development. How can the operations be achieved? Machine Learning Operations (MLOps) are achievable through Kubeflow as it helps with the scalable and portable deployment of ML workflows. In this webinar, learn about model maintenance, deployment, automation, and more through Kubeflow.

MLOps with Kubeflow
Join this Webinar to Gain Insights Into:
  • Overview of Kubeflow MLOps platform
  • End-to-End Model Deployment through Jupyter Notebooks on Kubeflow
  • Docker Image Creation using Fairing on Kubeflow
  • Model Deployment using KFServing on Kubeflow
  • Model Monitoring and Visualization using Tensorboard and Prometheus/Grafana on Kubeflow
  • Model Training & Serving Pipeline using Argo on Kubeflow

  • Jupyter Notebook to Argo Pipeline using Kale on Kubeflow
  • Q & A

Tahir Javed

Solutions Architect at Royal Cyber Inc

Nikhil John

Chief Growth Officer at Royal Cyber Inc

Watch On-Demand