Predictive modeling for early success forecasting of movies using Video-On-Demand streaming data, featuring Gradient Boosting Machines and advanced feature engineering techniques.
This repository provides a comprehensive Exploratory Data Analysis (EDA) of entertainment content, revealing trends in relation to audience preferences, production locations, release patterns and content duration.
Power BI dashboard analyzing 3.4K+ web series (2000–2024) across 42 countries, 96 industries, and 70M+ votes.
Machine learning pipeline for predicting movie box office success. Includes web scraping, data pipelines, feature engineering, ML models, MLflow tracking, and a web interface for predictions.
Comprehensive SQL analysis of Netflix content library with 15 advanced queries exploring movies vs TV shows, ratings, genres, directors, actors, and regional content distribution.
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