Welcome to the Student Marks Predictor web application repository! This application allows you to predict student marks using a machine learning algorithm, all wrapped up in a sleek Flask-powered frontend. 📚🔮 Whether you're an HTML/CSS enthusiast or a machine learning aficionado, this project showcases the seamless collaboration between both worlds.

• User-Friendly Interface: The frontend, crafted using HTML and CSS, offers a smooth and intuitive experience for users.
• Flask Backend Magic: The Flask backend seamlessly handles user requests and communicates with the machine learning model.
• Predictive Analytics at Play: Harness the power of a pre-trained machine learning model, specifically the Linear Regression algorithm, to predict student marks with high accuracy.
• Easy Deployment: Just clone this repository, install the dependencies with pip install -r requirements.txt, run python app.py, and access the app through your web browser. It's that simple!

1. Clone the Repository: Grab a local copy of this repository using git clone https://github.com/your-username/student-marks-predictor.git.
2. Install Dependencies: Navigate to the project folder and run pip install -r requirements.txt to install the necessary packages.
3. Run the App: Execute python app.py to start the app.
4. Access the App: Open your web browser and head to http://localhost:5000 to see the magic unfold!

Contributions are warmly welcomed! 🙌 If you discover any bugs or have ideas for improvements, please don't hesitate to submit an issue or pull request. Let's make this project even better together!

This project is licensed under the MIT License.

Disclaimer: Please note that this project is intended for educational purposes only. The machine learning model predictions are based on sample data and should not be used for actual decision-making.

Created with ❤️ by Keshav Kumar Jha.

Connect with me on LinkedIn: LinkedIn Profile

🚀 Happy predicting! 🎓🔥