ML Fundamentals and Metrics

Goal: Learn overfitting, underfitting, and the bias-variance tradeoff, plus which metrics actually matter for imbalanced problems (precision, recall, ROC-AUC, not accuracy), so you can prove a model works and pick the right metric for the job.

Do:

1. Watch the video above ⬆️

2. Complete this course https://developers.google.com/machine-learning/crash-course