Model tracker: Monitor performance metrics of deployed models
Track model versions, deployment dates, and performance metrics easily with model tracker to enhance machine learning operations.
Fill out one or more form fields
Comprehensive solution for monitoring deployed model performance metrics
Optimize your workflow with efficient input management
Intuitive text-based input fields
Easily capture essential details about your deployed models with user-friendly input fields. Enter the model name, version number, deployment date, monitoring frequency, performance metrics, alert thresholds, responsible team member's name, and additional comments to ensure no critical information is overlooked.
Enhance model oversight through structured monitoring
Leverage structured monitoring options to track vital performance metrics such as accuracy and precision. By setting up tailored monitoring frequencies and alert thresholds, you can proactively address potential model issues and ensure the reliability of your deployments.
Streamlined collaboration for team efficiency
Facilitate collaboration among Machine Learning Engineers, Data Scientists, and ML Ops Specialists by capturing accountability details within the input forms. By designating a responsible team member for each model, you can enhance communication and accountability across your analytics and data science teams.
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Additional information
Best for: Machine Learning Engineer, Model Monitoring Specialist, Data Scientist - Model Deployment, ML Operations Engineer, Data Analytics Consultant