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SMS SPAM CLASSIFICATION

This is the Capstone project for the Course "IT3160E - Intro to AI" of Asso. Prof. Than Quang Khoat

Table of Contents

Installation

Required packages: matplotlib, numpy, pandas, skikit-learn, pipeline, nltk, hyperopt

Usage

Run the main.html file to test on our web interface. Since the spam messages in the training data are quite long, it is recommended to use text of 20-word or more.

We deploy and train data using 6 different settings (3 models x 2 feature extraction techniques) and perform hyperparameter tuning within the Notebook.ipynb file. You can also find some data visualization there.

Configuration

- 1. In root, run 'pip install -q -r requirements.txt' to install all the required packages
- 2. Open the file 'main.html' in your browser
- 3. Enter your SMS into the box, then simply click 'Check'. You can find some examples within the 'sample.txt' file.

Contributing

Tran Viet Anh - 20226013

Tuong Phi Tuan - 20226069

Thibault Erwan Ludovic Lecordier - 2023T014

Adrien Monteiro - 2023T012

Diego De Sousa - 2023T013

About

This is the capstone project for the "Intro to AI" course

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