Infographic showing the workflow of Machine Learning for Root Cause Analysis, from data collection to ML models and root cause identification, with iiqedu.org watermark in the top-right corner.
AI & Machine Learning in QC/QA, Machine Learning for Root Cause Analysis, Uncategorized

Machine Learning for Root Cause Analysis

/

This infographic demonstrates the workflow of Machine Learning for Root Cause Analysis (ML-RCA). It starts with data collection from logs, sensors, and metrics, followed by data preprocessing and feature engineering. The diagram highlights the application of ML models — including supervised learning, unsupervised learning, and anomaly detection — to identify the likely root causes of failures. The workflow also includes feedback loops for continuous learning. The top-right corner features a subtle watermark: iiqedu.org.