Wine quality prediction

This project is a part of my Small Projects series with the objective of taking a practical approach into machine learning.

Project Status: On-Hold

Project Intro

The purpose of this project is to predict wine quality based on different set of features. Using for this objective UCI ML White wine dataset

Methods used

• Data Visualization
• Linear Regression
• Lasso Regression
• Random Forest
• Grid Search
• Cross validation

Technologies

• Pandas
• Jupyter Notebook
• Scikit learn
• Scipy

Notebooks

• Exploratory Data Analysis on UCI wine dataset (under development)
• Regression for Wine quality prediction
• Stacking models and gradient boosting for wine quality prediction (backlog)