This is a project from my Machine Learning class in which a couple colleagues and I tried to predict the quality of wine using various Machine Learning algorithms.
The basic skeleton of the three models was created by my teammates, while I heavily editted them to give them a similar presentation. Originally, each python file only contained one model that read the red and white wine data together. However, due to a lack of accuracy on the neural network, it was decided that we should make seperate models, one for each class of wine, and I took it upon myself to implement those changes.
Anyways, to run the files, it is important to first install numpy, sklearn, and tensorflow.keras. There are a variety of ways that this can be done, but I recommend using pip. Open your command line of choice, and type:
pip install numpy pip install sklearn pip install tensorflow
This should be enough to run the projects.
Special thanks to Dr. Eicholtz from Florida Southern College, who taught us the class and how to use the libraries, as well as Dr. Paulo Cortez at the University of Minho in Guimarães, Portugal, for gathering the wine data we used.