Inspiration
As a student, I often find myself distracted while trying to study—whether it’s Instagram, Facebook, movies, or other interruptions. To address this challenge, I decided to create a Student Recommendation System. With the help of AI and my own knowledge, I built a web application designed to help students learn with focus and minimal distractions.
What It Does
The system allows students to select a subject and topic from a wide range of options. It then curates the best information from the internet and presents it in a clear, distraction-free format. Additionally, it tracks study streaks, hours studied, and highlights the most frequently chosen subjects.
How We Built It
The project was developed using VS Code and primarily leverages scikit-learn, with AI integration to enhance recommendations and personalization.
Challenges We Faced
Funding: Limited resources to hire additional developers.
Time: Balancing college coursework with project development. I typically work on this project twice a week.
Accomplishments
We are proud that the system is already running successfully on localhost, demonstrating its core functionality.
What We Learned
This project has been a tremendous learning experience, deepening our understanding of AI, machine learning, and practical application development.
What’s Next for the Student Recommendation System
Our vision is to make this platform as engaging and widely used as social media apps like Instagram. Next steps include:
Developing a mobile application.
Integrating a chatbot to provide interactive learning support.
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