https://github.com/mariooohzc/gender-prediction-datacamp-project

https://github.com/mariooohzc/gender-prediction-datacamp-project

Last synced: 26 days ago
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• Host: GitHub
• URL: https://github.com/mariooohzc/gender-prediction-datacamp-project
• Owner: mariooohzc
• Created: 2024-01-19T10:22:43.000Z (11 months ago)
• Default Branch: master
• Last Pushed: 2024-01-19T12:19:48.000Z (11 months ago)
• Last Synced: 2024-12-01T16:55:57.187Z (26 days ago)
• Language: Jupyter Notebook
• Size: 698 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Gender Prediction using sounds

This project identifies the gender of best selling authors from 2008 to 2017 listed out by the New York Times.

The datasets used in this project is directly obtained from DataCamp.

Given the potential for names to share similar pronunciations despite variations in spelling, the fuzzy library is utilised to check if two names sound the same. The babynames_nysiis.csv, which contains the unique NYSIIS versions of baby names and the corresponding genders, is cross-referenced with the NYSIIS equivalent of the author's first name.

The result of this project show that there are more female authors than male authors on the New York Times best seller's list throughout the years, 2008 - 2017.