Q.19 What are three types Machine learning Model Monitoring?1. Service, Drift and Accuracy Monitoring2. Docker3. Data transformation4. Deployment, Monitoring, Lifecycle & Governance
Question
Q.19 What are three types Machine learning Model Monitoring?1. Service, Drift and Accuracy Monitoring2. Docker3. Data transformation4. Deployment, Monitoring, Lifecycle & Governance
Solution
The three types of Machine Learning Model Monitoring are:
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Service Monitoring: This involves keeping track of the performance and functionality of the machine learning model in a production environment. It includes monitoring the response time, throughput, and availability of the model.
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Drift Monitoring: This involves monitoring the changes in the input data over time. If the input data drifts too far from the data the model was trained on, the model's performance may degrade. Drift monitoring helps to identify this issue early.
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Accuracy Monitoring: This involves monitoring the accuracy of the model's predictions. If the model's accuracy decreases over time, it may be necessary to retrain the model with new data.
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