Week 10/11 - Machine Learning
Our final task was to create two charts produced by different machine learning techniques: one supervised and one unsupervised.
For my unsupervised machine learning task, I wanted to see if a dendogram would group similar fruit together from a dataset I found containing information about size, mass, and colour. Google colab notebook available here.
The algorithm was mostly successful, although noticeably oranges are not clustered together and some of the red apples appear to be mixed in the middle with some of the oranges.
For my supervised machine learning task, I wanted to see if my project dataset could accurately predict the Recidivism Rate in the US. The Google Colab Notebook can be accessed here.
The model did not have much success in predicting the Recidivism Rate from the data, with a calculated mean squared error of 285.