After finishing a recent Fake News Classification Project, I wanted to build a simple webapp that used my model.
After finishing a recent Fake News Classification Project, I wanted to build a simple webapp that used my model. Because of their ease of implementation, I chose to build the app with Streamlit and deploy it with Heroku. While there is a lot more that can be done with both platforms, what follows are step by step instructions to get started with a simple project using my app as an example.
Please note that Streamlit requires Python 3.6 or later.
pip install streamlit
After installation is complete, test it out the installation with the built in ‘hello world’ app.
If everything is working ok, this will open a window in a browser with a web page that offers several demos.
You can then return to your terminal window and stop Streamlit with control-c.
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As a part of a Machine Learning project, in this article, I will show you Fake News Detection Model with Machine Learning. I will use all the misinformation. Fake News is one of the major concerns in our society right now. It is a very widespread issue that even the most leading media sometimes gets with the trap of Fake News. If it’s difficult for media channels to detect fake news then it’s next to difficult for a general citizen. As a part of a Machine Learning project, in this article, I will show you Fake News Detection with Machine Learning. I will use all the misinformation that we heard from some previous months about coronavirus. So at the end of this article, you will be able to create a fake news detection model on coronavirus.
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