Machine Learning 편집하기 (부분)

==Types of Machine Learning==
Machine learning is typically categorized into several types based on the way models learn from data:
*'''Supervised Learning''': Models are trained on labeled data, where each input is paired with the correct output. Commonly used for classification and regression tasks.
*'''Unsupervised Learning''': Models work with unlabeled data, discovering hidden patterns and relationships without explicit instructions. Often used in clustering, association, and dimensionality reduction.
*'''Semi-Supervised Learning''': Combines labeled and unlabeled data to improve model performance, useful when labeling data is expensive or time-consuming.
*'''Reinforcement Learning''': An agent learns by interacting with an environment, receiving rewards or penalties, and optimizing actions to maximize rewards. Applied in robotics, gaming, and self-driving cars.