This project is about the prediction of red wine quality using different machine learning algorithms
These datasets can be viewed as classification or regression tasks. The classes are ordered and not balanced (e.g. there are much more normal wines than excellent or poor ones).
Predict the quality of red wine using π‘ Machine Learning models. Features π data preprocessing, π EDA, and π§ models like Random Forest and Linear Regression for precise predictions based on chemical properties. Cheers to data science! π₯
This repository stored the output of IBM SPSS's multiple linear regression and factor analysis of red wine quality dataset. The dataset used is from Kaggle (https://www.kaggle.com/uciml/red-wine-quality-cortez-et-al-2009). The software used in this repository is IBM SPSS 26
This project is about the prediction of red wine quality using different machine learning algorithms
Add a description, image, and links to the red-wine topic page so that developers can more easily learn about it.
To associate your repository with the red-wine topic, visit your repo's landing page and select "manage topics."