Do you want to learn how to monitor the performance of your models in the AWS, safely and securely within your environment?

Wiljan will walk us through how to catch model failure using the nannyML cloud and the importance of monitoring models post-deployment.

Learn how to easily deploy and integrate your monitoring system via the AWS Marketplace. Ensure a complete monitoring workflow that:

- Automatically collects data in production (new)
- Estimates Model Performance
- Detects concept shift (new)
- Detects multivariate data drift
- Monitors Data Quality

Timestamps:
0:00 Introduction
0:30 Agenda
1:10 AWS Setup
1:42 NannyML offerings
2:20 Prerequisites
4:20 Kubernetes cluster setup
6:28 Cloud subscription
7:10 License configuration
9:10 Creating access role
10:14 NannyML helm chart download
11:20 NML Cloud deployment
12:40 Trial license
14:08 NML Cloud instance access
20:04 NML Cloud instance setup
24:08 Adding a model
26:42 Model overview
28:31 Model summary
30:09 Performance analysis
31:27 Covariate shift analysis
34:01 Data quality analysis
34:46 Adding a model via SDK
37:50 Realized performance analysis
38:30 Concept shift analysis
39:58 Conclusions

Would you like to know more about NannyML? Check out our website👇
https://www.nannyml.com/
Also, we are fully open-sourced, so don’t forget to star us on Github! ⭐️
https://github.com/nannyml/nannyml