This project is a spam classifier implemented in Python, utilizing Machine Learning and Deep Learning algorithms such as Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Logistic Regression, Neural Networks, Naive Bayes, and LSTM. The classifier effectively distinguishes between spam and non-spam emails by leveraging Natural Language Processing (NLP) preprocessing techniques with NLTK. The project focuses on evaluating the performance of each algorithm based on accuracy and execution time.
- BeautifulSoup4
- Matplotlib
- NLTK
- NumPy
- Pandas
- Scikit-learn
- Torch