Quality of Analysis for Machine Learning
Project description
QoA4ML - Quality of Analytics for ML
Source code
https://github.com/rdsea/QoA4ML
Probes
- QoA4ML Probes: libraries and lightweight modules capturing metrics. They are integrated into suitable ML serving frameworks and ML code
- Probe properties:
- Can be written in different languages (Python, GoLang)
- Can have different communications to monitoring systems (depending on probes and its ML support)
- Capture metrics with a clear definition/scope
- e.g., Response time for an ML stage (training) or a service call (of ML APIs)
- Thus output of probes must be correlated to objects to be monitored and the tenant
- Support high or low-level metrics/attributes
- depending on probes implementation
- Can be instrumented into source code or standlone
QoA4ML Reports
This module defines QoA_Client
, an object that will gather metrics from probes and client information, create simple reports and send it to handler
Examples
https://github.com/rdsea/QoA4ML/tree/main/example
Change Log
0.0.13 (18/04/2022)
First Release
0.0.18 (10/05/2022)
Update system metric
Project details
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