SMS Spam Classifier

Overview

A simple Machine learning and NLP based Web Application which classify the given messages as Spam or Ham(Not Spam) built using Flask and deployed on Heroku.

• To view the Deployed Application, click on the link given below : SMS Spam Classifier Web Application : https://sms-spam-predictor-nlp.herokuapp.com/

• To get the Code for Exploratory data analysis/visualisations, Text-Processing, different algorithms used and the model evaluation, click on the link mentioned below : Link of jupyter notebook - https://github.com/asthasharma98/Data-Science/blob/main/SMS-Spam-Classifier/SMS%20Spam%20Classifier%20.ipynb

A Demo of the Web App :

Technical Aspect

This Project is mainly divided into two parts:

1. Exploring the dataset, Preprocessing texts and traning the model using Sklearn.
2. Building and hosting a flask web app on Heroku.

About the repository Structure :

• Project consist app.py script which is used to run the application and is engine of this app. contians API that gets input from the user and computes a predicted value based on the model.
• prediction.py contains code to build and train a Machine learning model.
• templates folder contains two files main.html and result.html which describe the structure of the app and the way this web application behaves. These files are connected with Python via Flask framework.
• static folder contains file style.css which adds some styling and enhance the look of the application.

Installation

The Code is written in Python 3.8. If you don't have Python installed you can find it here. If you are using a lower version of Python you can upgrade using the pip package, ensuring you have the latest version of pip. To install the required packages and libraries, run this command in the project directory after cloning the repository:

pip install -r requirements.txt 

To clone the repository

git clone https://github.com/asthasharma98/SMS-Spam-Classifier-Deployment.git

Run

To Run the Application

python app.py

Deployement on Heroku

Install Heroku CLI as this makes it easy to create and manage your Heroku apps directly from the terminal. You can download it from here.

next step would be to follow the instruction given on Heroku Documentation to deploy a web app.

Technologies used

Future work

• Improve model performance.
• Try to collect more samples of text messages with the help of users input.