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As mentioned earlier, we have Organizations at the highest level,  which contain Workspaces. Within each workspace, you can create and manage Projects.

A project represents the ML use case you want to solve eg. Loan status prediction, house sale prediction

Data Summary

Once you upload data, AryaXAI automatically performs a comprehensive analysis of the added datasets for your initial file. This analysis includes data profiling, data modeling, and explainability.

Data Summary table offers an overview of the total data volume and unique features.

Accessing the Data Summary table:

To view the summary of data features and the data types through SDK:


project.data_observations('Training') # Can pass any Tag for getting Summary

The Data Warning section highlights any inconsistencies detected in the uploaded analytical data. These warnings encompass various issues, including missing data, high feature correlation, high cardinality, and more.

You can also retrieve the data warning specifically by 'tag'. Just pass the 'Tag' below.


# data diagnosis
project.data_warnings('Training')

As mentioned earlier, we have Organizations at the highest level,  which contain Workspaces. Within each workspace, you can create and manage Projects.

A project represents the ML use case you want to solve eg. Loan status prediction, house sale prediction

Data Summary

Once you upload data, AryaXAI automatically performs a comprehensive analysis of the added datasets for your initial file. This analysis includes data profiling, data modeling, and explainability.

Data Summary table offers an overview of the total data volume and unique features.

Accessing the Data Summary table:

To view the summary of data features and the data types through SDK:


project.data_observations('Training') # Can pass any Tag for getting Summary

The Data Warning section highlights any inconsistencies detected in the uploaded analytical data. These warnings encompass various issues, including missing data, high feature correlation, high cardinality, and more.

You can also retrieve the data warning specifically by 'tag'. Just pass the 'Tag' below.


# data diagnosis
project.data_warnings('Training')