Understanding the distinction between classification and regression is crucial for effective machine learning applications. When detecting fraud, the choice between a binary classification (yes or no) and a risk score (quantitative) hinges on the specific business needs. Training involves updating model parameters from a random initialization, which is similar to fine-tuning pre-trained models, emphasizing the importance of decision-making in model deployment.
