SentimentAnalysisWithMLandPython

It analyzes the given article and parses it for sentiment analysis.

Usage example

• Open Google Collab

• Upload the .ipynb file.

• Goto #Load the data cell and load the CV and Job Description as docx file.

• Upon running the respective cells the last cell produces the following output.

  The Article is [Positive] or [Negative] or [Neutral]

Release History

• 0.1.0

  • The first proper release

• 0.0.1

  • Work in progress

Meta

Anirudh Tulasi – @AnirudhTulasi – [email protected]

Contributing

1. Fork it (https://github.com/anirudhtulasi/PythonScraper/fork)
2. Create your feature branch (git checkout -b feature/fooBar)
3. Commit your changes (git commit -am 'Add some fooBar')
4. Push to the branch (git push origin feature/fooBar)
5. Create a new Pull Request