This is a GitHub project that focuses on SMS spam classification. The project aims to develop a machine learning model that can accurately classify SMS messages as either spam or not spam.
SMS spam is a common problem faced by many individuals. This project aims to provide a solution by developing a machine learning model that can effectively classify SMS messages as spam or not spam. By accurately identifying spam messages, users can better manage their inbox and avoid potential scams or unwanted messages.
To use this project, you need to have Python installed on your. You can follow these steps to get started:
- Clone the repository:
git clone https://github.com/ShowRounak/SMS-Spam-Classification.git
- Install the required dependencies:
pip install -r requirements.txt
Once you have installed the necessary dependencies use the project by running the following command:
streamlit run app.py
The project uses the SMS Spam Collection Dataset from Kaggle. The dataset contains a collection of SMS messages labeled as spam or ham (not spam).
Dataset Link: https://www.kaggle.com/datasets/uciml/sms-spam-collection-dataset
- SMS spam classification using machine learning.
- Preprocessing techniques for cleaning and transforming text data.
- Training and evaluation of multiple machine learning models.
- GUI using Streamlit
- MlFlow integration