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evidentlyai · Oct 12, 2023 · 6a91f58 · 6a91f58
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 * [Module 2: ML monitoring metrics](ml-observability-course/module-2-ml-monitoring-metrics/readme.md)
   * [2.1. How to evaluate ML model quality](ml-observability-course/module-2-ml-monitoring-metrics/evaluate-ml-model-quality.md)
   * [2.2. Overview of ML quality metrics. Classification, regression, ranking](ml-observability-course/module-2-ml-monitoring-metrics/ml-quality-metrics-classification-regression-ranking.md)
-  * [2.3. Evaluating ML model quality CODE PRACTICE](ml-observability-course/module-2-ml-monitoring-metrics/ml-model-quality-code-practice.md)
+  * [2.3. Evaluating ML model quality [CODE PRACTICE]](ml-observability-course/module-2-ml-monitoring-metrics/ml-model-quality-code-practice.md)
   * [2.4. Data quality in machine learning](ml-observability-course/module-2-ml-monitoring-metrics/data-quality-in-ml.md)
-  * [2.5. Data quality in ML CODE PRACTICE](ml-observability-course/module-2-ml-monitoring-metrics/data-quality-code-practice.md)
+  * [2.5. Data quality in ML [CODE PRACTICE]](ml-observability-course/module-2-ml-monitoring-metrics/data-quality-code-practice.md)
   * [2.6. Data and prediction drift in ML](ml-observability-course/module-2-ml-monitoring-metrics/data-prediction-drift-in-ml.md)
-  * [2.8. Data and prediction drift in ML CODE PRACTICE](ml-observability-course/module-2-ml-monitoring-metrics/data-prediction-drift-code-practice.md)
+  * [2.8. Data and prediction drift in ML [CODE PRACTICE]](ml-observability-course/module-2-ml-monitoring-metrics/data-prediction-drift-code-practice.md)
 * [Module 3: ML monitoring for unstructured data](ml-observability-course/module-3-ml-monitoring-for-unstructured-data.md)
 * [Module 4: Designing effective ML monitoring](ml-observability-course/module-4-designing-effective-ml-monitoring.md)
 * [Module 5: ML pipelines validation and testing](ml-observability-course/module-5-ml-pipelines-validation-and-testing.md)