A for Analytics

AI Model Monitoring and Support

We consider several metrics for evaluating our model's performance to make sure that we deliver the best service to our clients. If our model had some performance issues, then we provide the right support to uplift the performance of our model.

Artificial intelligence services

AI Model Monitoring and Support

AI Model Monitoring and Supporting

We at A for Analytics provide the best AI model monitoring and supporting services, where we closely watch and evaluate the performance of AI models we created and evaluate the way it operates in our client’s business.

Our Approach to Machine Learning Model Monitoring

We consider the following metrics to evaluate our model’s performance: 

Data drifts 

Data drifts are a critical metric for model monitoring, where a change in data or the inclusion of new data might affect the model’s performance.  

Performance shifts 

here we evaluate the performance of our model, by analyzing the way it operates with real-time data, and we compare the predictions it makes with actual results and provide required support if necessary. 

Health aspects 

Health aspects cover checking the wellness of involved physical devices like CPU, memory disk, etc. which might not sound important, but we pay heed to it as a part of our machine learning model monitoring.

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Integrated data 

It involves checking the relevancy, accuracy, and importance of involved datasets, since the entire operation is based on data, a complete cross-check will be carried out with the data reliability. 

Segmentation 

Segmentation-based model monitoring helps to know about the ins and outs of a model’s performance, for instance, if a model is deployed on an eCommerce store and it estimates a higher price for a specific category, then its accuracy needs to be rechecked.