https://github.com/mednour2019/ia-scrap-bb-dja

Machine Learning Scraping and Sentiment Analysis of Breaking Bad Reviews
https://github.com/mednour2019/ia-scrap-bb-dja

css django html machine-learning python scrapping selenuim

Last synced: about 1 month ago
JSON representation

Machine Learning Scraping and Sentiment Analysis of Breaking Bad Reviews

• Host: GitHub
• URL: https://github.com/mednour2019/ia-scrap-bb-dja
• Owner: mednour2019
• Created: 2024-07-26T19:51:56.000Z (6 months ago)
• Default Branch: master
• Last Pushed: 2024-11-28T19:09:15.000Z (about 1 month ago)
• Last Synced: 2024-11-28T20:21:04.212Z (about 1 month ago)
• Topics: css, django, html, machine-learning, python, scrapping, selenuim
• Language: Jupyter Notebook
• Homepage: https://prtfnour.vercel.app/pdf-viewer/pdf-project-description.html?project=project20
• Size: 5.58 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Machine Learning Scraping and Sentiment Analysis of Breaking Bad Reviews

# The project is in master Branch

# Description

For my exam project, I chose to scrape reviews and apply machine learning techniques. Specifically, I focused on Breaking Bad reviews. I scraped the data and processed it using Python to handle null values and duplicates. I then generated a machine learning model to achieve high accuracy. The project includes a detailed sentiment analysis based on this model to ensure precision. Additionally, I developed a Django application that allows users to enter reviews and predicts whether the sentiment is neutral, positive, or negative.

![Screen Shot](https://prtfnour.vercel.app/images/portfolio/project20.JPG)

## Demo Video

Check out the demo video of the project [here](https://drive.google.com/file/d/132fIlK4UPp2DjSucoqCeY37EwkhtCDE8/view?usp=sharing)

## Features

- 🧩 Scraping Data with BeautifulSoup and Selenium: Collect reviews from multiple sites using BeautifulSoup and Selenium.

- 🧩 Unify Data in One Data Source via Python: Merge and clean the scraped data into a single, unified data source using Python.

- 🧩 Machine Learning Process and Treatment: Process the data for machine learning, handling null values and duplicates.

- 🧩 Apply Machine Learning Algorithms: Implement and train machine learning models to analyze sentiment with high accuracy.

- 🧩 Download Blob Model for Prediction: Save the trained machine learning model as a blob for prediction purposes.

- 🧩 Inject Model into Django Interface: Integrate the machine learning model into a Django application for real-time predictions.

-  🧩User Review Input and Prediction Display: Allow users to input reviews in the Django interface and display the predicted sentiment (neutral, positive, or negative).

## Getting Started

### Prerequisites

- Python

- DJANGO

- Machine learning

- Scrapping Data

- Html

- Css

- Selenuim

- Beautiful Soup

## Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.

1. Fork the Project

2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)

3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)

4. Push to the Branch (`git push origin feature/AmazingFeature`)

5. Open a Pull Request

## License

Distributed under the MIT License. See `LICENSE` for more information.

## Contact

Mohamed Nour KHammeri - [@My-Web-Site](https://prtfnour.vercel.app) - [email protected]

Project Link: [https://github.com/mednour2019/IA-scrap-bb-dja](https://github.com/mednour2019/IA-scrap-bb-dja)