https://github.com/filsan-musa/Project-Twitter_Bot_Detection

Using a synthetic dataset from Kaggle, generated with Python's Faker library to mimic real Twitter data, we train several classical machine learning models (ie. classical classification algorithms, as well as ensemble methods)to identify bots from real users.
https://github.com/filsan-musa/Project-Twitter_Bot_Detection

data-preprocessing decision-trees ensemble-model feature-engineering gradient-boosting-classifier gridsearchcv logistic-regression random-forest-classifier randomsearchcv

Last synced: 3 months ago
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Using a synthetic dataset from Kaggle, generated with Python's Faker library to mimic real Twitter data, we train several classical machine learning models (ie. classical classification algorithms, as well as ensemble methods)to identify bots from real users.

• Host: GitHub
• URL: https://github.com/filsan-musa/Project-Twitter_Bot_Detection
• Owner: filsan95
• Created: 2024-08-18T02:52:19.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2024-08-29T00:00:52.000Z (almost 2 years ago)
• Last Synced: 2024-12-31T22:25:27.421Z (over 1 year ago)
• Topics: data-preprocessing, decision-trees, ensemble-model, feature-engineering, gradient-boosting-classifier, gridsearchcv, logistic-regression, random-forest-classifier, randomsearchcv
• Language: Jupyter Notebook
• Homepage: https://www.kaggle.com/datasets/goyaladi/twitter-bot-detection-dataset
• Size: 1.84 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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