GoogleCloudPlatform/vertex-ai-samples
Dec 2024 – Dec 2024
1 Month active
Languages Used
PythonSQL
Technical Skills
BigQueryData MonitoringFeature StorePython SDKVertex AI
alicechang0909
PROFILE
Alicechang0909
Developed automated monitoring for Vertex AI Feature Store to enhance data quality and model reliability, focusing on data drift detection and feature monitoring. Leveraged BigQuery for data integration and used Python and SQL to create a Feature Group and Feature, configuring end-to-end monitoring workflows within a Colab notebook. Incorporated automated cleanup steps to ensure reproducibility and simplify resource teardown. All work was contributed to the GoogleCloudPlatform/vertex-ai-samples repository, enabling reuse and collaboration across teams. No major bugs were reported during the development period, and the implementation was documented thoroughly to support review and future enhancements by other contributors.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
953
Activity Months1
Your Network
4737 peopleSame Organization
@google.com4703
Benedict OdaiMember
Craig IngramMember
KayyuriMember
Scott SuarezMember
Agent2Agent (A2A) BotMember
Andreas AbelMember
Aadi KapurMember
Aadish GoelMember
Aahil MehtaMember
Shared Repositories
34
Work History
December 2024
1 Commits • 1 Features
Dec 1, 2024For 2024-12, delivered automated Vertex AI Feature Store monitoring to improve data quality and model reliability. Implemented feature monitoring and data drift detection via Feature Monitors, created a Feature Group and Feature backed by BigQuery data, and configured end-to-end monitoring with a Colab-based workflow. Included cleanup steps in the Colab notebook to ensure reproducibility and easy teardown. All work is tracked in GoogleCloudPlatform/vertex-ai-samples, enabling reuse across teams.
1 Commits • 1 Features
Dec 1, 2024For 2024-12, delivered automated Vertex AI Feature Store monitoring to improve data quality and model reliability. Implemented feature monitoring and data drift detection via Feature Monitors, created a Feature Group and Feature backed by BigQuery data, and configured end-to-end monitoring with a Colab-based workflow. Included cleanup steps in the Colab notebook to ensure reproducibility and easy teardown. All work is tracked in GoogleCloudPlatform/vertex-ai-samples, enabling reuse across teams.
December 2024
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonSQL
Technical Skills
BigQueryData MonitoringFeature StorePython SDKVertex AI
Repositories Contributed To
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