Skip to content

This project implements preprocessing, feature engineering, and multiple machine learning models to build a robust genre classification system.

Notifications You must be signed in to change notification settings

04bhavyaa/movie-genre-prediction

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Movie Genre Prediction

This project aims to predict the genre of a movie based on its plot summary. Leveraging Natural Language Processing (NLP) and machine learning techniques, the system processes textual data and applies various models to achieve accurate predictions.

Directory Structure:

Directory structure:
└── 04bhavyaa-movie-genre-prediction/
    ├── app.py
    ├── artifacts.dvc
    ├── data/
    │   ├── train_data.txt
    │   ├── test_data_solution.txt
    │   ├── description.txt
    │   └── test_data.txt
    ├── requirements.txt
    ├── genre-classification.ipynb
    └── README.md

Tech Stack:

  • Libraries: Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, NLTK
  • Models: Logistic Regression, Linear SVC, Random Forest, Naive Bayes
  • Best Performing Model: Ensemble of Linear SVC and Logistic Regression with an accuracy of 58.88% on the validation set.

Key Takeaways:

  • Ensemble models outperformed individual models due to combined decision-making.
  • Fine-tuning hyperparameters significantly improved accuracy for individual models.
  • Preprocessing steps like lemmatization and scaling were essential for handling text data.

App Gallery:

Screenshot 2024-12-22 162608 Screenshot 2024-12-22 162643

About

This project implements preprocessing, feature engineering, and multiple machine learning models to build a robust genre classification system.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published