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The notebooks demonstrate a basic sentiment analysis application using TF-IDF for feature extraction and Logistic Regression for sentiment classification, designed to work across languages. The notebooks cover model development and servicing of an ML model on PythonAnywhere, with an API encapsulated using Swagger UI. The API is implemented using Flask and the model available via Binder. These elements showcase a full pipeline from model development to deployment.