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Cornell ORIE 4741 Course Project: Machine Learning with Big Messy Data

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box-office-gross-prediction

Song Tang (st883), Wenchang Yang(wy286), Jia Rao (jr2254)

Project in ORIE 4741 - Machine Learning with Big Messy Data, Cornell University

The decision making process for a person who is planning to see a movie might sound like this: What are movies in theaters now about? How do people rate them on Metacritic or Rotten Tomatoes websites? The person may search on Google for more information before purchasing the ticket. Moviegoers are now more actively exploring different movie options online.

In this project, The objective is to use these information to predict box office performance of the opening weekend prior to its release date. In this way, movie marketers can adjust post-release marketing strategies based on accurate predictions: if the prediction of opening weekend performance is high, they may decide to release the movie in more theaters during the opening weekend in hopes of revenue growth.

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Cornell ORIE 4741 Course Project: Machine Learning with Big Messy Data

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