Prediction-of-Wine-Quality

For this project, I used Kaggle’s Red Wine Quality dataset to build various classification models to predict whether a particular red wine is “good quality” or not. Each wine in this dataset is given a “quality” score between 0 and 10. For the purpose of this project, I converted the output to a binary output where each wine is either “good quality” (a score of 7 or higher) or not (a score below 7). The quality of a wine is determined by 11 input variables:

Fixed acidity Volatile acidity Citric acid Residual sugar Chlorides Free sulfur dioxide Total sulfur dioxide Density pH Sulfates Alcohol Objectives

The objectives of this project are as follows:

To experiment with different classification methods to see which yields the highest accuracy To determine which features are the most indicative of a good quality wine Steps included in this project:

Importing Lib Loading Data Understanding Data Missing Values Exploring Variables(Data Anylasis) Feature Selection Proportion of Good vs Bad Wines Preparing Data for Modelling Applying different models Choosing right model Hurray you just completed the task ! CHEERS!