What is Kubernetes | Kubernetes Explained | AI and ML Workflows with Kubernetes
This tutorial will give an overview of Kubernetes and the development of AI/ML workflows with it.
Data science and machine learning are helping to drive business decisions and generate income and insights for organizations across a spectrum of industries, from oil and gas to financial services and many in between. However, developing and deploying ML workflows can be challenging.
In this session, we'll explore how to incorporate data science and AI/ML into Kubernetes development workflows, taking advantage of the platform's openness and rich ecosystem. Using well-known open-source tools for data science such as Jupyter Notebooks and TensorFlow, we will explore different strategies to accelerate and automate ML workloads with Kubernetes.
Table of Content
00:00 – Introduction
06:04 – AI/ML people
07:30 – A day in the life of a data scientist
10:06 – Kubernetes
12:18 – MLOps: DevOps to ML
15:35 – OpenDataHub
17:24 – OpenShift Data Science
17:53 – Demo
44:58 – Resources
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