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Analyzed box office data from Box Office Mojo, exploring relationships between worldwide revenue, release year, and a combined score that considers both factors. It includes visualizations like scatter plots, bar charts, and identifies top and bottom performing movies.
My first solo data science project! A simple project built using linear regression to predict box office success for movies using data I scraped myself.
Box Office App made in react where you can search for shows and actors comes with 2 themes - Dark Mode & Light Mode. You can star your favorite shows for future. You can also download the app on your desktop or mobile.
This project started after diving deep into the dataset used on datacamp.com for this guided project https://www.datacamp.com/projects/740 Disney Movies and Box Office Success I wanted to dive deep into the original dataset. From here I created the first notebook where I made an analysis of best-selling movies and most prolific directors, but mo…
Python project employing machine learning to predict revenue for movies using Kaggle data from the since-concluded "TMDb Box Office Prediction" Playground Prediction Competition.
GCP hosted product for over 1 million movie investors on HSX.com, aiding online movie trading and box-office investments by leveraging Big Data technologies like Hive and Hadoop, and Tableau dashboards
Given the social media buzz the movie is generating and the people involved in the movie production, can we predict the revenue it’ll generate once it’s out?