spam-classifier-webserver

A Flask based webserver which accepts text from user through webservice, and generates prediction whether the text is spam or ham.

The data is a collection of SMS messages tagged as spam or ham that can be found here. First, we will use this dataset to build a prediction model that will accurately classify which texts are spam.

Naive Bayes classifiers are a popular statistical technique of e-mail filtering. They typically use bag of words features to identify spam e-mail. Therefore, We’ll build a simple message classifier using Naive Bayes theorem.

Installation

Run the following command on the root dorectory of this project.

Optional commands to create virual environment to install dependency:

1. Create virtual environment: 'python -m venv spamclassifier'
2. Activate virual environment: 'spamclassifier\Scripts\activate'

Command to start server:

1. install dependency: 'pip install -r requirements.txt'
2. flask run This will start flask based spam classifier server in production mode.

To access home page browse to http://localhost:5000

To start python notebook from within python virtual environment follow below commands:

1. ipython kernel install --user --name=spamclassifier
2. jupyter notebook
3. open DataModelling&NaiveBayesModel.ipynb from browser.

NOTE: if you are running multiple kernels in jupyter notebook, switch to spamclassifier kernel from kernel->change kernel->spamclassifier from browser.

web app routes:

1. localhost:5000\train will load dataset and create vocabulary, train Naive Bayes model using it.
2. localhost:5000\ or localhost:5000\index is the main page of the web app.
3. localhost:5000\predict will predict the class of text passed. This api will load trained model which were created from 1st url and use it for prediction.

References:

1. https://anbasile.github.io/programming/2017/06/25/jupyter-venv/