UbiOps Demonstration: Manage deployments, pipelines, training experiments, environments and storage

UbiOps is developed for data scientists and teams who are looking for an easy and production-ready way to train and then deploy and run their Python or R models as live services in the cloud.

UbiOps takes care of containerization of your code, deploying it as a microservice with its own API endpoint, request handling and automatic scaling. There are also advanced features for creating data pipelines, model training and tracking, code environment management, file storage, version management, job scheduling, monitoring, security and governance.

Chapters:
0:00 Introduction
0:36 Set up your account and how you will interact with UbiOps
1:51 Get started with a deployment
3:24 Run your code using a request
4:38 Storage
5:16 Chain multiple deployments together as pipelines
6:29 Standardize code environments
7:07 Train your models in UbiOps
9:42 Conclusion

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UbiOps homepage: https://ubiops.com/
Documentation: https://ubiops.com/docs/
Create an account: https://ubiops.com/sign-up/