End-to-end wiring using Kubeflow, Kafka and ElasticSearch

Presented by

Vinod Kumar, Dir Field Engineering Dir. and Aymen Frikha, Sr Field Engineer

About this talk

Open source technologies, like Kubeflow, are increasingly being used for AI/ML and predictive modeling across industries. However, operationalising the model and building the AI/ML infrastructure requires planning, automation and a lot of DevOps resources. Our latest webinar provides real world application in finserv ai, with a demo on building and training an AI/ML model on bare metal using MAAS, Kubeflow, Kafka and ElasticSearch to predict whether the S&P 500 will close positive or negative on the current day, drawing on past data. Canonical engineers also provide details on the operations-side of AI/ML, with infrastructure considerations, automation tooling and additional services available. In this webinar you will learn: Details of an ML, production use case for end-to-end wiring using multiple applications Demo of building and training an AI/ML model for predicting S&P performance Highlight additional solutions and tooling to implement, secure and manage open source technologies in production
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