/Wine_Quality_Prediction

Primary LanguageJupyter NotebookMIT LicenseMIT

Wine_Quality_Prediction

Prerequisites to contribute:

  • Python
  • Jupyter Notebooks (Installation guide: https://jupyter.org/install kindly install the 'classic Jupyter Notebook' if you don't already have it)
  • Basic Data Science and Machine Learning techniques/algorithms, Exploratory Data Analysis

Kindly go through "CONTRIBUTING.md" before starting out on the issues :)

Is this beginner friendly?

YES! Apart from beginner and intermediate level issues, there are also open ended issues which can be approached by all levels of data scientists and ML experts :)

What if I have a problem?

Contact any of the ACM Team members!

Dataset:

The Data set contains the following columns

1 - fixed acidity

2 - volatile acidity

3 - citric acid

4 - residual sugar

5 - chlorides

6 - free sulfur dioxide

7 - total sulfur dioxide

8 - density

9 - pH

10 - sulphates

11 - alcohol

12- Quality

Citation:

P. Cortez, A. Cerdeira, F. Almeida, T. Matos and J. Reis. Modeling wine preferences by data mining from physicochemical properties. In Decision Support Systems, Elsevier, 47(4):547-553, 2009.

Incase of any issues, get in touch with the maintainer at pradish.k1812@gmail.com Hacknight participants please contact us on the Discord channel for Wine Prediction in case of queries

Maintainer: Pradish Kapur

This is an Official Repository for ACM PESUECC's event Hacknight 2.0 2020!