Machine Learning Overview
Learn core ML tasks, model families, and metrics for evaluation. Understand data splits, overfitting, and regularization.
📚 Tasks
- Classification: predict labels
- Regression: predict continuous values
- Clustering: discover groups
- Dimensionality reduction: compress while preserving structure
❓ Frequently Asked Questions
1) Overfitting?
Model memorizes noise; use regularization and validation.
Model memorizes noise; use regularization and validation.
2) Cross-validation?
Resampling to estimate generalization performance.
Resampling to estimate generalization performance.
3) Metrics?
Accuracy, F1, ROC-AUC, RMSE depending on task.
Accuracy, F1, ROC-AUC, RMSE depending on task.
4) Feature scaling?
Normalize to aid gradient-based methods.
Normalize to aid gradient-based methods.