A wine dataset is provided. The task is to analyze data and build a regression model to predict the quality of the wine.
- Description of data
- Preprocess data
- Visualize data
- Build a Regression model
- Check Regression Assumptions
- Goodness of fit
- Compare different Regression methods
- Name of the data: Wine data from UCI Machine learning repository
- Number of data points: 4898
- Number of features: 11
- Target attribute: Quality of wine
- Range of target attribute: 3 to 9
- Wine data
- Link to the report(detailed analysis) - Report
- Source code can be found on Kaggle