TikTok-Claims-Classification-End-to-End-Analysis-and-Modeling Cyberoctane29 · COMPLETED
This project involves analyzing TikTok videos to classify claims vs. opinions using Python. It includes EDA, statistical tests, logistic regression, and ML models (Random Forest, XGBoost) to support content moderation. Built with pandas, scikit-learn, and Tableau, the solution helps TikTok automate content review and enhance moderation efficiency.
github.com/Cyberoctane29/TikTok-Claims-Classification-End-to-End-Analysis-and-Modeling · ★ 6 · Forks 0 · Size 26.4 MB
SUMMARY
Technologies 1
Scored 1
Observed 1
Practices 6
Evidence 1
Skips 0
COVERAGE
Analyzed 27 files · 163 commits · 0 API calls
TECHNOLOGIES & DEPTH
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · absentcontinuous_integration · absentcontainerization · absentlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2024-12-04
Last commit 2026-07-27
Active months 9
Commits 163