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observabilitymodel-monitoringml-observabilityevaluationdrift-detection

Arize AI

Arize AI is an ML observability platform that helps monitor model performance, detect drift, and troubleshoot issues. It offers real-time monitoring, embedding analysis, and automated alerts to ensure optimal AI system performance.

intermediate30 min5 steps
The play
  1. Explore Arize AI Platform
    Visit the Arize AI website to explore the platform's features and capabilities. Focus on understanding the key components like real-time monitoring, embedding analysis, and automated performance alerts.
  2. Sign Up for a Free Account
    Sign up for a free Arize AI account to gain hands-on experience with the platform. This will allow you to explore the interface and understand how to integrate your models.
  3. Integrate a Sample Model
    Follow the Arize AI documentation to integrate a sample model into the platform. This step involves sending model predictions and actuals to Arize AI for monitoring.
  4. Analyze Model Performance
    Use the Arize AI dashboard to analyze the performance of your integrated model. Explore metrics like accuracy, precision, recall, and drift to identify potential issues.
  5. Set Up Performance Alerts
    Configure automated performance alerts within Arize AI to receive notifications when your model's performance degrades below a specified threshold. This proactive monitoring helps you address issues quickly.
Starter code
No specific starter code is applicable as Arize AI requires integration with your existing ML models. Refer to Arize AI documentation for integration guides and code examples.
Source
Arize AI — Action Pack