Closed abhisheks008 closed 2 years ago
Full name : Rahul Kumar GitHub Profile Link : https://github.com/rahul-netizen Participant ID : 740 Approach for this Project : First do an EDA then find more about Passive Aggressive Classifier, then try models which work best with text data Are you a participant of SWOC 2.0? YES
Issue assigned to you @rahul-netizen
ML-Crate Repository (Proposing new issue)
:red_circle: Project Title : Fake News Detection :red_circle: Aim : Build a fake news detection model with Passive Aggressive Classifier algorithm. The Passive Aggressive algorithm can classify massive streams of data, it can be implemented quickly. :red_circle: Dataset : https://www.kaggle.com/c/fake-news/data :red_circle: Approach : Try to use 3-4 algorithms to implement the models and compare all the algorithms to find out the best fitted algorithm for the model by checking the accuracy scores. Also do not forget to do a exploratory data analysis before creating any model.
Hello, ML-Crate contributors, this issue is only for the contribution purposes and allocated only to the participants of SWOC 2.0 Open Source Program.
π Follow the Guidelines to Contribute in the Project :
requirements.txt
- This file will contain the required packages/libraries to run the project in other machines.Model
folder, theREADME.md
file must be filled up properly, with proper visualizations and conclusions.:red_circle::yellow_circle: Points to Note :
:white_check_mark: To be Mentioned while taking the issue :
Happy Contributing π
All the best. Enjoy your open source journey ahead. π