The problem ReHash solves

Reading large documents/articles can be time-consuming as well as a tedious task. Most people tend to avoid reading just after looking at the length of a document.
To tackle the above problem we are making a text summarizer. Using Machine Learning and Deep Learning we create a model that takes a large text as input such as the input of an article and returns a text that is a summary of the above text. For instance, if we enter the text that contains around 1000 words, then our model would try to summarize it under 300 words. In the model, we used Tf-isf for keeping the frequency of words and tried to implement Restricted Boltzman Machine(RBM) to make the model more accurate. We would deploy our model on a web app to provide a better user experience. The web app is developed using flask and the database used is SQL. We are using libraries like flask_bcrypt for encrypting passwords and flask_mail for mailing services.