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Understand Edge MLOps

Recorded Webinar

Understand Edge MLOps - Life-cycle Management of ML in the Edge

About This Webinar

The use of machine learning (ML) models is becoming more and more common in industrial IoT applications, especially for use cases such as anomaly detection and predictive maintenance.

In this webinar we will introduce you to remote deployment and life-cycle management of ML models running at the edge. Using the Crosser Edge Director to radically simplify the orchestration of edge deployments at scale.

Welcome to Crosser webcasts - Where Edge Analytics meets Industry 4.0

Agenda

  • Collect and prepare data to deliver results with your ML model
  • Test and train ML models for edge deployments
  • Deploy and maintain your ML model on one or many devices

About the author

Goran Appelquistran (Ph.D) | CTO

Göran has 20 years experience in leading technology teams. He’s the lead architect of our end-to-end solution and is extremely focused in securing the lowest possible Total Cost of Ownership for our customers.

“Hidden Lifecycle (employee) cost can account for 5-10 times the purchase price of software. Our goal is to offer a solution that automates and removes most of the tasks that is costly over the lifecycle.

My career started in the academic world where I got a PhD in physics by researching large scale data acquisition systems for physics experiments, such as the LHC at CERN. After leaving academia I have been working in several tech startups in different management positions over the last 20 years.

In most of these positions I have stood with one foot in the R&D team and another in the product/business teams. My passion is learning new technologies, use it to develop innovative products and explain the solutions to end users, technical or non-technical."

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