TMDB 5000 Movies Analysis

This repository consists of the jupyter files for analysis on the TMDB 5000 Movies dataset.

Report: Link

Files

main.ipynb: Exploratory data analysis where we analyze the trends between different attributes in the dataset.

KNN_Regression.ipynb: KNN regression on movie revenue.

KNN_Classification.ipynb: KNN classification on movie revenue while comparing it across different bucket sizes.

Overfitting.ipynb: Looking at overfitting and underfitting with KNN regression on movie revenue.

Irrelevant.ipynb: Hypothesis testing for significance of irrelevant deemed attributes.

Autocorrelation.ipynb: Hypothesis testing for Spatial Autocorrelation in No. of movies and Average rating.

OTT.ipynb: Test availability of movies on diferent OTT Platforms using self defined metrics.

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
ott		ott
.gitignore		.gitignore
Autocorrelation.ipynb		Autocorrelation.ipynb
Irrelevant.ipynb		Irrelevant.ipynb
KNN_Classification.ipynb		KNN_Classification.ipynb
KNN_Regression.ipynb		KNN_Regression.ipynb
OTT.ipynb		OTT.ipynb
Overfitting.ipynb		Overfitting.ipynb
README.md		README.md
Report.pdf		Report.pdf
main.ipynb		main.ipynb
tmdb_5000_credits.csv		tmdb_5000_credits.csv
tmdb_5000_movies.csv		tmdb_5000_movies.csv