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Movie Revenue & Ratings Prediction Using 5000 IMDB Movies [Python, Machine Learning, GitHub]

License: MIT License

Jupyter Notebook 99.40% Python 0.60%
machine-learning prediction-algorithm regression-algorithms predictive-modeling regression-models revenue-prediction rating-prediction movie-revenue movie-ratings movie-rating-prediction

movie-revenue-rating-prediction-from-imdb-movie-data's Introduction

Movie Revenue & Rating Prediction from IMDB Movie Database

Domain : Artificial Intelligence, Machine Learning
Sub-Domain : Supervised Learning, Classification
Techniques : Predictive Modeling, Prediction, Regression Modeling, Regression, Feature Expraction, Preprocessing, Visualizeation, Feature Engineering

Description

  1. Developed regression model for predicting movie revenue and ratings from 5000 movie data.
  2. Performed data analysis, visualization, feature extraction, cleaning (missing value, anomaly), preprocessing (rescaling, normalization, feature transformation (one hot encoding)) and trained with cross-validation.
  3. With 28 numerical, textual and categorical features attained regression error (Mean Squared Error) 0.005 on scale of 1 for revenue.

Random Forest:

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Decision Tree:

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Languages : Python
Tools/IDE : Anaconda
Libraries : NumPy, Pandas

Duration : October - December 2016

Current Version : v1.0.0.0

Last Update : 10.11.2016

movie-revenue-rating-prediction-from-imdb-movie-data's People

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Forkers

ani6 muhammedsara mdaburummanrefat mctozal mokhlesurrahman ftkhanft akarsh17 zoyt123

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