Kubernetes for AI, Machine Learning, and Deep Learning

Presented by

Sam Charrington, Founder & Industry Analyst, TWIML; Nanda Vijaydev, Lead Data Scientist, HPE

About this talk

Join this webinar with Hewlett Packard Enterprise and TWIML ​–​ a community and podcast focused on AI and Machine Learning (ML) ​–​ as we explore the use of Kubernetes for AI / ML deployments in the enterprise. As organizations mature in their use of AI and ML, they need to build repeatable, efficient, and sustainable processes for model development and deployment. Containers and Kubernetes provide essential building blocks to help operationalize these processes and support ML Operations (MLOps). In this webinar, we will discuss: -The challenges of moving from pilot to production with Machine Learning and Deep Learning, at enterprise scale -How containers and Kubernetes can help address these challenges, as a foundation for MLOps -Lessons learned and best practices from enterprises who have successfully leveraged Kubernetes for AI / ML Register today and you'll receive the accompanying TWIML e-book on deploying Kubernetes for Machine Learning, Deep Learning, and AI.

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Hewlett Packard Enterprise (HPE) is transforming how enterprises deploy AI / Machine Learning (ML) and Big Data analytics. HPE’s container-based software platform makes it easier, faster, and more cost-effective for enterprises to innovate with AI / ML and Big Data technologies – either on-premises, in the public cloud, or in a hybrid architecture. With HPE, our customers can spin up containerized environments within minutes, providing their data scientists with on-demand access to the applications, data, and infrastructure they need.