This repository will walk you through training a text classification model using TF-IDF and NaiveBayes classifier.

The model is then deployed as a flask app and the app is then subsequently dockerized.

The data used to train this model is obtained from the following Kaggle repository: https://www.kaggle.com/uciml/sms-spam-collection-dataset

According to their website, "The SMS Spam Collection is a set of SMS tagged messages that have been collected for SMS Spam research. It contains one set of SMS messages in English of 5,574 messages, tagged acording being ham (legitimate) or spam."

The original dataset can be found here. https://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection

The creators would like to note that in case you find the dataset useful, please make a reference to previous paper and the web page: http://www.dt.fee.unicamp.br/~tiago/smsspamcollection/ in your papers, research, etc.

We offer a comprehensive study of this corpus in the following paper. This work presents a number of statistics, studies and baseline results for several machine learning methods.

Almeida, T.A., Gómez Hidalgo, J.M., Yamakami, A. Contributions to the Study of SMS Spam Filtering: New Collection and Results. Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11), Mountain View, CA, USA, 2011.

Some of the code for the flask app POST and GET methodologies were inspired by the tutorials from the following link: https://scotch.io/bar-talk/processing-incoming-request-data-in-flask

The MIT License (MIT)

Copyright (c) 2020 Ahmed Sherif

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

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