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This project aims to predict customer churn for a subscription-based service using historical customer data. By analyzing features like usage behavior and customer demographics, we can build a modeβ¦
The model is trained on the "Genre Classification Dataset" from Kaggle. It uses a TF-IDF vectorizer to convert the text data into numerical features and then employs three different classifiers to β¦
This project builds a machine learning model to classify SMS messages as "spam" or "ham" (legitimate). It includes a Jupyter Notebook for model development and a Flask web application for live deteβ¦