https://github.com/yonatanadam/film-success-prediction

Analyzing Hollywood movie success based on genre, target audience, and runtime using machine learning
https://github.com/yonatanadam/film-success-prediction

data-analysis ipynb machine-learning

Last synced: 28 days ago
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Analyzing Hollywood movie success based on genre, target audience, and runtime using machine learning

• Host: GitHub
• URL: https://github.com/yonatanadam/film-success-prediction
• Owner: YonatanAdam
• License: mit
• Created: 2024-08-11T13:19:48.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-08-11T13:25:51.000Z (3 months ago)
• Last Synced: 2024-10-11T15:40:14.481Z (28 days ago)
• Topics: data-analysis, ipynb, machine-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 765 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Movie Success Analysis

## Project Description

Part of my School Computer Science final project.

This project explores the relationship between the genre, target audience, and length of Hollywood films and their success. The analysis aims to identify patterns and predictors of success using machine learning techniques.

## Research Question

Is there a relationship between the genre of the film, the target audience, the length of the film, and the success of Hollywood films?

## Dataset

The dataset was sourced from [Kaggle Movies Dataset](https://www.kaggle.com/datasets/danielgrijalvas/movies). It includes information on various Hollywood movies such as budget, gross earnings, genre, runtime, and more.

## Installation

To set up the project environment, follow these steps:

* Clone the repository:

   ```sh

   $ git clone https://github.com/yourusername/movies-success-analysis.git

   $ cd movies-success-analysis

   ```

* Run it in vscode or in Google Colab or any place that can run .ipynb files.