https://github.com/nishant2018/book_recommendation

This project deploys a book recommendation system using Flask API, requiring Flask, pandas, scikit-learn, numpy, and joblib. It consists of a Jupyter Notebook for model building, an app.py file for APIs, and HTML/CSS templates for user interface. Users input preferences on the homepage and receive book recommendations.
https://github.com/nishant2018/book_recommendation

Last synced: 3 days ago
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This project deploys a book recommendation system using Flask API, requiring Flask, pandas, scikit-learn, numpy, and joblib. It consists of a Jupyter Notebook for model building, an app.py file for APIs, and HTML/CSS templates for user interface. Users input preferences on the homepage and receive book recommendations.

• Host: GitHub
• URL: https://github.com/nishant2018/book_recommendation
• Owner: Nishant2018
• Created: 2023-12-31T01:08:55.000Z (11 months ago)
• Default Branch: master
• Last Pushed: 2024-08-20T07:57:48.000Z (3 months ago)
• Last Synced: 2024-08-20T18:10:30.474Z (3 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 39.2 MB
• Stars: 4
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
**Deploying Book Recommendation System using Flask**   

This project demonstrates the deployment of a Book Recommendation System using Flask API.   

**Prerequisites**

Ensure that you have the following packages installed:

- Flask==2.0.0

- pandas==2.2.1   

- scikit-learn==0.24.2    

- numpy==1.24.3       

- joblib==1.0.1  

   

**Project Structure**

This project consists of the following parts:

1. `book_recommendation.ipynb`: Contains the code for building the book recommendation model.

2. `app.py`: Flask application containing APIs to receive user input and provide book recommendations.

3. `templates`: Folder containing HTML templates:

   - `index.html`: Allows users to input preferences and receive book recommendations.

4. `static`: Folder containing CSS stylesheets:

   - `style.css`: Provides styling for the HTML templates.

**Running the Project**

1. Navigate to the project directory.

2. Create the book recommendation model by running the command:

   ```

   python book_recommendation.ipynb

   ```

   This will generate a serialized version of the model named `book_recommendation_model.pkl`.

3. Run the Flask application by executing:

   ```

   python app.py

   ```

   The Flask app will start running on port 5000 by default.

4. Open your web browser and navigate to:

   - `http://127.0.0.1:5000/` or `http://localhost:5000/` to access the homepage.

   - `http://127.0.0.1:5000/predict` to view the output of the book recommendation system.

**Usage**

1. On the homepage, enter your preferences for book recommendations.

2. Click on the "Recommend Books" button.

3. You will receive a list of recommended books based on your preferences.

**Note**

Ensure that you have a stable internet connection to access the book recommendations.