This project aims to predict the quality of wine using machine learning techniques. We utilize a dataset from Kaggle and employ a Random Forest Classifier to make predictions.
The dataset used in this project is obtained from Kaggle and contains various physicochemical properties of red wine along with their quality ratings. You can find the dataset in repo.
To run this project, you need to have the following libraries installed: numpy pandas scikit-learn matplotlib seaborn jupyter
Data Preprocessing Model Training Model Evaluation
The results of the model evaluation are Training Data Accuracy : 100% Test Data Accuracy : 85% The trained model is bit overfit but as this a simple project for learning it does not affect much
Deployment The application is deployed using Streamlit. You can access it here = https://ml-project-6-wine-quality-prediction-vpwk6uj5u6itbv9fixptt2.streamlit.app/
Contributions are welcome! Please feel free to submit a Pull Request.