• Features
• Challenges
• Accomplishments
• Installation
• Demo of the Project

Our application automates the generation of university recommendations and Google Play Store recommendations by leveraging user input and a Kaggle dataset. This makes the recommendation process user-friendly and efficient.

Our chatbot is designed to break down language barriers in education. It translates text into four languages, enhancing global accessibility to university and app recommendations.

We curate the highest quality university and app recommendations based on the Kaggle dataset, ensuring that users have access to valuable and relevant information.

Our application enables users to contribute their own recommendations and feedback, fostering a collaborative and dynamic environment for knowledge sharing.

We aim to revolutionize how users access university recommendations and discover apps on the Google Play Store. Our platform makes learning and app exploration more accessible and efficient, regardless of linguistic boundaries.

During the development of our application for university recommendations and Google Play Store recommendations, we encountered several challenges:

• Data Utilization 🌐: Effectively using the Kaggle dataset to provide accurate recommendations required careful consideration and implementation.

• Multilingual Support 🗣️: Developing a chatbot capable of accurate translations across multiple languages demanded significant effort.

• Content Curation 📽️: Curating top-quality recommendations for universities and apps necessitated meticulous attention to detail.

• User Contributions 📝: Enabling user-generated content while maintaining content quality and integrity presented unique challenges.

We're proud of the following accomplishments:

• A user-friendly application for university and app recommendations.

• A multilingual chatbot that enhances global accessibility.

• Curation of high-quality recommendations.

• Empowering users to contribute and collaborate.

• Striving to revolutionize the way people access educational and app-related information.

To run StudyClub locally, follow these steps:

1. 🔱 Clone the repository:

git clone https://github.com/Vikash-8090-Yadav/Study-Club.git

2. 🗂️ Navigate to the project directory:

 cd Study-Club

3. 🗂️ Navigate to Backend

 poetry run python3 textbase/textbase_cli.py test uni.py

7. 🗂️ Move to the frontend directory:

 poetry run python3 textbase/textbase_cli.py test main.py

Uni: https://www.kaggle.com/datasets/alitaqi000/world-university-rankings-2023 App:https://www.kaggle.com/datasets/lava18/google-play-store-apps

This project is licensed under the MIT License - see the MIT file for details.

Vikash Kumar Yadav