This project is a basic model using sklearn methods to predict Penguin species based on beak size and sex. It is inspired by Moshfegh Hamedani of Programming with Mosh who did the same project, but to predict preferred music genre from sex and age. The project includes a jupyter notebook file with all of the code to load and process the data as well as train, analyze, and test the model. The file also creates a .dot file which generates an included visualisation of the model's decision tree. The repository includes this .dot file and corresponding image as well as the .joblib file (containing the model) and of course, the data itself.

This was my first real taste of an independent machine learning project - I was involved in a past project involving ML to predict chat-bot input data about various categories, but I was not as hands on as I'd have liked. I really just wanted to get a better sense of ML and work a bit more with sklearn using data that I was interested in. I found this dataset by searching through kaggle (and Google) for 'good machine learning data' and ended up selecting it because I haven't been able to work with animal/zoology data yet.