AI/ML

Easy and simple ML/DL model building and learning

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Cloud-friendly environment for ML model development

Manage your machine learning models and data on Kubernetes-based MLOps platform. You can automate the entire ML pipeline from model development, training to deployment, so it becomes easier to create, configure, or re-use ML models.

Benefits

Cloud Native MLOps Environments
Supports Kubeflow, an open source MLOps platform built on Kubernetes. On Kubeflow, you can conveniently manage models and data or use various open source tools on a unified Kubeflow-native MLOps environment.
Development Productivity Enhancement in Standardized Environment
Various machine learning frameworks from Tensorflow, Pytorch, Scikit-learn to Keras are supported on Kubeflow. Repetitive tasks across ML pipeline from model development, learning to deployment can be automated end-to-end, making it easier to create, configure, or re-use models.