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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