This is my capstone project for the computer science bachelors program at Western Governors University. The project explores the extent to which machine learning can be used to accurately classify mushrooms as edible or poisonous based on entered mushroom attributes. The end goal is to create a web application that can theoretically be used by mushroom foragers, if the results are compelling enough. A PDF of the detailed write up and the Jupyter Notbook used to explore data can both be viewed in the root directory.
The project's topic is to classify mushrooms as edible or poisonous by using machine learning algorithms. This is done by analyzing different characteristics of the mushrooms.
The data used in this project is mushrooms.csv, a collection of over 8,000 mushroom species, classified as edible or poisonous, along with 22 of their attributes ranging from cap shape to odor.
To use the final application, simply visit c964.pythonanywhere.com, no installations are needed. Test different combinations of characteristics and see how well the algorithm predicts the class of the mushroom.