Lesson 6.1: Evaluating Machine Learning Models

Evaluating models is like checking how well you understand a subject. Accuracy, precision, recall, and F1-score help us measure a model's performance. We also balance "learning by heart" (overfitting) with understanding (bias).

Lesson 6.2: Deploying Machine Learning Models

Deploying a model is like using a finished project. We can integrate our model into apps, websites, or other systems. It's important to consider fairness and ethical implications.