2ML Model Development

• 2.1Model Selection and Training

  Understand three model-building approaches on SageMaker (built-in algorithms, script mode/bring-your-own container, AutoML/JumpStart) and training-job basics. The starting point for "ML Model Development" in MLA-C01.

• 2.2Hyperparameter Tuning and Overfitting

  Understand hyperparameter search with SageMaker Automatic Model Tuning, overfitting vs. underfitting, and remedies like regularization and adding data.

• 2.3Model Evaluation Metrics

  Understand evaluation metrics for classification (accuracy, precision/recall, F1, AUC) and regression (RMSE, MAE, R-squared), the confusion matrix, and metric choice under imbalance.