Spam Message Detection -FastApi Application

Hello There, Welcome to Spam Message detection API application built on FastApi Framework using machine learning model RandomForestClassifier algorithm to predict whether a message is ham or spam.

Below are some key points about the application :

• Data set is pulled from Kaggle Dataset spam-text-message-classification
• Trained model using Logistic Regression and Random Forest Classifier for better accuracy and appropriate confusion matrix is plotted for each model to explain the accuracy.
• Random Forest Classifier showed better accuracy then Logistic Regression.
• Model is built and saved using Joblib library.
• All the input messages are passed to pipeline to vectorize the string using TfidfVectorizer then Random Forest Classifier.

Api's

1. localhost:8000/ : Prints the welcome message with output {'Hello': 'Welcome to the spam detection APP'}.
2. localhost:8000/spam_detection_path/{message} : Takes message variable as path parameter and predicts the whether input message is to spam or ham .