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Meta Data Science Case Competition [Top 5 Finalist Submission] - 2023 🌠. Key Tools: Gephi for Network Analysis, Matplotlib for Plotting, Scikit-Learn for Clustering, GPT-4 for Labeling.

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Meta Data Science Case Competition 2023

This is a quick showcase of a few things we were able to generate for the Meta Data Science Case Competition 2023 at UVA. The contest was a week long, and we were given a historical dataset of the Netflix catalog. We ended up using lots of outside data (TMDB, IMDB, Wikipedia, etc.) to generate our final suggestions that were on a 10 slide presentation.

Note: This was only my part of the project. Other Graphs and Visualizations were made by my teammates as well for the final presentation.

Network Graph of Netflix Talent (Connected by Worked With on a Project)

Network Graph of Netflix Talent

Node Size is Proportional to TMDB Popularity. Color is auto-identified by Gephi's community detection algorithm.

Isolation Index of Netflix Talent Most Popular Country Per Color

Animated (Open GitHub Pages to See) Map of Titles Added Semantically Clustered Through K-Means and Labeled by GPT with Descriptions.

Animated Map of Titles Added Semantically Clustered Through K-Means and Labeled by GPT with Descriptions

Number of Titles Per Production Country Over Time

Number of Titles Per Production Country Over Time

Misc Graphs Not Presented in Final Presentation

G1 G2 G3 G4 G5 G6

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Meta Data Science Case Competition [Top 5 Finalist Submission] - 2023 🌠. Key Tools: Gephi for Network Analysis, Matplotlib for Plotting, Scikit-Learn for Clustering, GPT-4 for Labeling.

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