Course Recommender System

Overview

This Python application serves as a basic course recommender system based on content-based filtering. It uses the Flask framework to create a web service that recommends courses to users based on their specified interests.

Features

• Recommendations Endpoint: The /recommendations endpoint accepts a user's email as a query parameter, retrieves their interests from a MongoDB database, and generates course recommendations using content-based filtering.

• Content-Based Filtering: The recommender system uses TF-IDF vectorization and cosine similarity to calculate the relevance of courses to a user's interests.

• MongoDB Integration: User data and course information are stored in a MongoDB database, and the application leverages the pymongo library for database connectivity.

Getting Started:

• Clone Repository:

  git clone https://github.com/Hk669/course-recommendation-system.git
  

• Star the Repository🌟
  • click on the star at the top right

Create virtual environment

```bash
cd recommendations

python -m venv venv
.venv/Scripts/activate

pip install -r requirements.txt
```

Run the Flask API on 5000 port:

```bash
python course_recommender.py
```

API Usage

• Recommendations Endpoint:

  • URL: /recommendations
  • Method: GET
  • Parameters:
  • user_email (query parameter): User's email for fetching interests.
  • Response: JSON object containing recommended courses.

  GET http://127.0.0.1:5000/recommendations?user_email=testuser@gmail.com
  

• JSON Object :

  {"recommendedCourses": [
      { 
        "_id": "657dfd8327bd4eeac3b160de",
        "title": "Web Development for Begineers", "description":
        "This is a brand new web dev course for beginners",
        "slug": "web-development-for-begineers",
        "domain": "web development",
        "owner": "657d96853c49dea888c6e47d",
        "coverImage":
        "https://s3.ap-south-1.amazonaws.com/assets.advantagecommunity.in/course/1702755707016.jpg",
        "instructors": [],
        "price":0,
        "totalLectures": 20,
        "enrolledStudents": [],
        "sections": [],
        "ratings": [],
            "createdAt":"2023-12-16T19:41:55.196000",
            "updatedAt": "2023-12-16T19:41:55.196000",
            "__v": 0
            }
        ]
    }

---

License

This project is licensed under the MIT License.

Contact

If you have any queries, encounter issues, or need assistance, feel free to reach out to me.

Email: hrushikesh.dokala@studentambassadors.com

i'd greatly appreciate recieving some feedback. Thank you