Developed Email Spam Detector, compared Deep Learning, SVM, RF, XGBoost;
This repository contains code for an Email Spam Detector project. The project aims to develop a model to detect spam emails using various machine learning algorithms and conduct a comparative analysis of their performance.
Make sure you have the following software installed:
Python (version >= 3.6) Jupyter Notebook or any other Python IDE Required Python libraries (NumPy, Pandas, Scikit-learn, TensorFlow, XGBoost)
The dataset used for this project is not included in this repository due to its large size. However, you can obtain a suitable dataset from various public sources or use your own labeled dataset for training and evaluation.
The notebook will generate evaluation metrics (precision, recall, f1 score) for each model on the test dataset. The model with the best performance will be identified.