https://github.com/zenklinov/regression_logistic_-_sentiment_analysis_movie_data

This repository contains code for performing sentiment analysis using scikit-learn and logistic regression
https://github.com/zenklinov/regression_logistic_-_sentiment_analysis_movie_data

natural-language-processing nlp nltk scikit-learn sentiment-analysis

Last synced: 2 days ago
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This repository contains code for performing sentiment analysis using scikit-learn and logistic regression

• Host: GitHub
• URL: https://github.com/zenklinov/regression_logistic_-_sentiment_analysis_movie_data
• Owner: zenklinov
• License: apache-2.0
• Created: 2024-04-24T16:17:25.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-05-05T07:45:37.000Z (6 months ago)
• Last Synced: 2024-05-05T08:33:33.413Z (6 months ago)
• Topics: natural-language-processing, nlp, nltk, scikit-learn, sentiment-analysis
• Language: Jupyter Notebook
• Homepage:
• Size: 18.1 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Sentiment Analysis with Scikit-Learn

This repository contains code for performing sentiment analysis using scikit-learn and logistic regression.

## Contributors

- Amanatullah Pandu Zenklinov

## Source Project

This project is based on the Coursera course: [Perform Sentiment Analysis with scikit-learn](https://www.coursera.org/learn/scikit-learn-logistic-regression-sentiment-analysis/home/welcome).

## Files

- `sentiment_movie_reviews.ipynb`: Jupyter Notebook containing the code for sentiment analysis.

- `movie_data_csv.rar`: Compressed file containing the movie data CSV file.

- `LICENSE`: Apache-2.0 license file.

## Usage

1. Download the repository.

2. Extract the `movie_data.csv` file from `movie_data_csv.rar`.

3. Open and run the `sentiment_movie_reviews.ipynb` notebook to perform sentiment analysis.

## License

This project is licensed under the Apache-2.0 License. See the [LICENSE](LICENSE) file for details.