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:

|

Decision Tree:

| | | |

Languages : Python

Tools/IDE : Anaconda

Libraries : NumPy, Pandas

Duration : October - December 2016

Current Version : v1.0.0.0

Last Update : 10.11.2016