title	emoji	colorFrom	colorTo	sdk	sdk_version	app_file	pinned	short_description
Analytics-Vidhya Free-Courses	👁	pink	green	gradio	5.5.0	app.py	false	This is assignment for Analytics Vidhya Gen AI Intern

Analytics Vidhya: Free Course Search

This project is a Gradio-based web application that allows users to search for relevant courses on Analytics Vidhya. It uses a pre-trained sentence-transformer model to calculate the similarity between a user query and course titles, descriptions, and lesson content, presenting the most relevant courses based on the query.

Table of Contents

• Features
• Installation
• Usage
• Project Structure
• Technologies Used
• License

Features

• Course Search: Enter a query to find relevant courses from the dataset based on title, description, and lesson content.
• Similarity-Based Ranking: Courses are ranked by their similarity score, determined using cosine similarity.
• Interactive UI: Built with Gradio, making it easy to interact and retrieve search results.

Installation

Prerequisites

• Python 3.7+
• Git LFS for handling large files if the dataset file (courses_with_granular_embeddings.json) is over 10 MB.

Steps

1. Clone the Repository

   git clone https://huggingface.co/spaces/<username>/Analytics-Vidhya_Free-Courses.git
   cd Analytics-Vidhya_Free-Courses

2. Install Dependencies Install the necessary packages specified in requirements.txt:

   pip install -r requirements.txt

3. Set Up Git LFS (if required)

   git lfs install
   git lfs pull

4. Run the Application

   python app.py

Usage

1. Open the Gradio app on localhost or the designated Hugging Face Space link.
2. Enter a search query in the text box, and click "Submit" to find relevant courses.
3. Results will be displayed in a table format, showing course titles, descriptions, and links.

Project Structure

Analytics-Vidhya_Free-Courses/
├── app.py                    # Main application code
├── requirements.txt          # Dependencies required to run the app
├── courses_with_granular_embeddings.json  # Dataset with course embeddings
├── .gitattributes            # File to specify Git LFS-tracked files
├── README.md                 # Project README
└── preprocessing-files       # Folder containing scripts and files used for preprocessing course data
    ├── get_url.py               # Script to scrape URLs of free courses from Analytics Vidhya
    ├── scraper.py               # Script to extract detailed course data from each URL
    ├── free_course_links.json   # JSON file containing URLs of all free courses
    ├── free_courses_content.json # JSON file containing scraped details of each free course (title, description, curriculum)
    ├── create_embedding.py      # Script to generate embeddings for course titles, descriptions, and lessons
    ├── find_matching.py         # Script to find relevant courses based on user queries using similarity matching
    └── README.md                # Detailed documentation explaining the preprocessing steps and scripts

Technologies Used

• Gradio: For creating the interactive web interface.
• Sentence Transformers: For generating text embeddings to compare queries and course content.
• Scikit-Learn: For cosine similarity calculations.
• Git LFS: To manage large files like courses_with_granular_embeddings.json.

License

This project is not at all licensed.