Machine Learning has evolved well past being a buzz word. As Google’s businesses collect more data from more sources, the need to gain insightful data and perform meaningful analysis grows. There are many options available today to achieve this but their portability is often challenging. Today, many data scientists run their models on their laptops with a single GPU but when they outgrow this, they struggle to find ways to easily move their models to the cloud. Kubeflow provides a way to load ML workloads into a Kubernetes cluster and easily move the jobs from one machine or cluster to a much larger environment.
Publisher: Google Cloud
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