A Dagster-Powered Spam Filter

A Dagster-powered spam filter was built using a Bag of Words model, which uses lists of spam and non-spam messages to determine whether a message is spam or not. The model was trained on an SMS spam dataset from Kaggle and used to score new messages against a test dataset. A job was created in Dagster to rebuild the model every month by integrating user messages from the application and comparing it to the previous month's model. The updated model was saved to a file and stored in a database table to keep track of the current model, which is compared to the previous model to promote the new one if it scores better. The API endpoint was created using Flask to expose the spam filter to users, and testing was done using cURL to try different messages to see if they get flagged as spam.

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