Kubeflow – A Cloud-Native ML Toolbox
One of the most common hurdles with developing data science/ machine learning models is to design end-to-end pipelines that can operate at scale and in real-time. Data scientists and engineers are often expected to learn, develop, and maintain the infrastructure for their experiments.
In this lab, Salman will discuss the merits of using Kubeflow, an open source Kubernetes-based platform designed to abstract away non-Machine Learning related tasks while still giving you control.
A few of the things you’ll learn:
– Kubeflow Architecture and installation
– Creating an end-to-end orchestration machine learning experiment in Kubeflow pipeline
– Current use cases of Kubeflow and how teams from other industries have been utilizing the cloud to scale their machine learning operations”