Predictive modeling for early success forecasting of movies using Video-On-Demand streaming data, featuring Gradient Boosting Machines and advanced feature engineering techniques.
Comprehensive SQL analysis of Netflix content library with 15 advanced queries exploring movies vs TV shows, ratings, genres, directors, actors, and regional content distribution.
Power BI dashboard analyzing 3.4K+ web series (2000–2024) across 42 countries, 96 industries, and 70M+ votes.
A comprehensive Power BI dashboard providing analytical insights into movie industry data including box office performance, ratings, genres, director/actor metrics, and trends. Analyzes budget vs revenue, release timing impact, and audience preferences.
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.
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.
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