Skip to content

acmpesuecc/Wine_Quality_Prediction

Repository files navigation

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!

About

No description or website provided.

Topics

Resources

License

Code of conduct

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published