Hate speech is one of the serious issues we see on social media platforms like Facebook and Twitter, mostly from people with political views.In this project, we will walk through how to build an end-to-end hate speech detection system with Python.
To create an end-to-end application for the task of hate speech detection, we must first learn how to train a machine learning model to detect if there is hate speech in a piece of text.To deploy this model as an end-to-end application, we will be using the streamlit library in Python which will help us see the predictions of the hate speech detection model in real-time.
As we are using the streamlit library in Python here so we cannot run this application the same way we run other Python programs. we need to write the command mentioned below in your command prompt or terminal:
streamlit run filename.py
Once the above command is executed, it will open a link on our default web browser which will show an end-to-end application where we have to write some text and it will detect if the text contains hate speech, offensive language or not, as shown in the image below.
