The recording of our talk at the AI infrastructure alliance micro summit. This talk covers ClearML serving including monitoring and focuses on the importance of being able to trace the deployed model all the way back to the original experiment, code and data that were used to train it! One of the mayor advantages of a single tool end-to-end MLOps workflow.

💻 Get a server:

Get started by using our free tier servers: https://app.clear.ml
OR by hosting your own: https://github.com/allegroai/clearml-server

📄 Documentation on Fundamentals:

Get Started: https://clear.ml/docs/latest/docs/getting_started/ds/ds_first_steps
Pip Package / ClearML SDK: https://clear.ml/docs/latest/docs/clearml_sdk
ClearML Data: https://clear.ml/docs/latest/docs/clearml_data/clearml_data
ClearML Agent: https://clear.ml/docs/latest/docs/clearml_agent
Supported libraries for automagical integration: https://clear.ml/docs/latest/docs/integrations/libraries

✨ Follow us and star us!

Github page: https://github.com/allegroai/clearml
Twitter: https://twitter.com/clearmlapp
Slack Channel: https://join.slack.com/t/allegroai-trains/shared_invite/zt-c0t13pty-aVUZZW1TSSSg2vyIGVPBhg
LinkedIn: https://www.linkedin.com/company/clearml