As part of the Udacity Machine Learning Engineer Nanodegree this project was designed to analyze and interpret the performance of a model.
The key takeaways learned from this project are:
- How to use NumPy to investigate the latent features of a dataset.
- How to analyze various learning performance plots for variance and bias.
- How to determine the best-guess model for predictions from unseen data.
- How to evaluate a model's performance on unseen data using previous data.