In this solution we have tried to detect fake news from a set news feeds. The feeds, in the form of csv files contains the headers as news_text and label. In myproj-fakenews-test.ipynb file we have tested the news feed from myproj-fakenews-test.csv data file and myproj-fakenews-train.csv train file. We have done it details in myproj-fakenews-analysis.ipynb project. Again we collected data from myproj-Articles_scraper.ipynb project. Added that data to the myproj-fakenews-train.csv file. again tested the data through myproj-fakenews-test.ipynb.
Group Name 1
In this solution we have tried to detect fake news from a set news feeds. The feeds, in the form of csv files contains the headers as news_text and label. In myproj-fakenews-test.ipynb file we have tested the news feed from myproj-fakenews-test.csv data file and myproj-fakenews-train.csv train file. We have done it details in myproj-fakenews-analysis.ipynb project. Again we collected data from myproj-Articles_scraper.ipynb project. Added that data to the myproj-fakenews-train.csv file. again tested the data through myproj-fakenews-test.ipynb.
Jupyter Notebook 2197 Version:Current
Jupyter Notebook 2197 Version:Current License: Permissive (Apache-2.0)
TypeScript 536 Version:v0.3.7
TypeScript 536 Version:v0.3.7 License: Permissive (BSD-3-Clause)
Jupyter Notebook 330 Version:Current
Jupyter Notebook 330 Version:Current License: No License
Group Name 2
Jupyter Notebook 9702 Version:v7.0.0a11
Jupyter Notebook 9702 Version:v7.0.0a11 License: Others (Non-SPDX)
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