Скачать или смотреть 2.) Creating a workspace on TrueFoundry

#machinelearning #mlops #ai #deeplearning #deployment

Let’s get started with the TrueFoundry platform and make yourself familiar with the two major sections of Integrations, containing the cluster, and workspace. See how the platform looks and what steps are needed to get started with a project here. Truefoundry's platform can be connected to multiple clusters and your Kubernetes cluster could be running in AWS on GCP, Azure, or anywhere else - we provide easy integration. Use various parameters such as access controls, limitations on the resources, etc. of the subclusters within each workspace. Then finally, learn how to add more people to the same workspace to work in collaboration.

00:00 Getting familiar with clusters on the Integrations tab
01:00 Creating a demo Workspace
03:07 Adding collaborators to the workspace


ABOUT THE HOST

Srihari Radhakrishna is a Senior ML Engineer at TrueFoundry. With a passion for creating exceptional interfaces for ML production, he strives to bridge the gap between complex algorithms and user-friendly experiences. Recognising the potential of generative AI, he is currently immersed in exploring how this cutting-edge technology can revolutionize software development.

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ABOUT TRUEFOUNDRY

TrueFoundry is a cross-cloud machine learning deployment PaaS that enables enterprises to speed up model testing and deployment while maintaining full security and control for the Infra/DevSecOps team. We enable machine learning teams to deploy and monitor models in 15 minutes with 100% reliability and scalability, saving money and allowing models to be released into production faster, resulting in genuine business value. We deploy on the customer's infrastructure, taking data privacy and other security concerns into consideration.

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