Wine Quality Predictor
Python
Django
NumPy & Pandas
Jupyter
JWT
Lessons learned
1
Machine Learning Integration
Developed and integrated machine learning models to predict wine quality based on various features.
2
Web Application Development
Built a user-friendly web interface using Django, allowing users to input wine characteristics and receive quality predictions.
3
Data Handling
Utilized NumPy and Pandas for efficient data processing and manipulation.
4
Frontend Design
Implemented responsive design principles using HTML and Bootstrap to ensure accessibility across devices.
Key Technologies
Python
Primary programming language used.
Django
Web framework for building the application's backend.
NumPy & Pandas
Libraries for numerical computations and data manipulation.
Jupyter
For developing and testing machine learning models.
HTML & Bootstrap
Technologies used for the frontend interface.
Access & Availability
