Supervised Learning
(การเรียนรู้แบบมีผู้สอน)
Definition
Supervised Learning (การเรียนรู้แบบมีผู้สอน) Hard Skill
A machine learning approach where models are trained on labeled data to make predictions or classifications based on input-output pairs.
Expertise Level
Level 1
Basic
1. Understands the basic concept of supervised learning and labeled datasets.
2. Can distinguish between input features and output labels.
3. Familiar with common supervised learning tasks such as classification and regression.
Level 2
Intermediate
1. Can implement common supervised learning algorithms like linear regression, decision trees, and support vector machines.
2. Understands model evaluation techniques such as cross-validation and performance metrics (accuracy, precision, recall).
3. Able to preprocess data and handle issues like missing values or feature scaling.
Level 3
Advanced
1. Designs and optimizes complex supervised models for high performance in real-world scenarios.
2. Applies feature engineering and selection techniques to improve model effectiveness.
3. Can interpret model outputs and explain decisions using advanced methods like SHAP values or LIME.
