Spam Email Detection using Decision Tree Classifier focuses on building a machine-learning model to classify email messages as either spam or not spam (ham). The dataset used contains email messages labeled with their respective categories. The primary goal is to create an effective spam detection system using natural language processing and machine learning techniques. The model is only capable of predicting the given inputs from the user. For the given input, the model can detect whether the input is a spam message or not.
Project Explanation, Requirements, and Project setup details are given inside the project folder.
