This project focuses on analyzing red wine quality using machine learning techniques. The dataset consists of physicochemical attributes of red wine, and the goal is to build predictive models that classify wine quality based on these features.
Note: This project is still a work in progress.
This notebook covers:
- Loading and exploring the red wine dataset
- Performing data preprocessing and feature engineering
- Training and evaluating machine learning models to predict wine quality
- Visualizing key insights from the dataset
- Exploratory data analysis and feature engineering
- Application of machine learning algorithms for classification
- Model evaluation using accuracy and performance metrics
- Data visualization for understanding wine quality distribution