Supervised learning is one of the most commonly used approaches in Machine Learning, where models learn from labeled datasets. This means that the input data has corresponding correct outputs, allowing the model to learn relationships and patterns over time. Supervised learning is widely used for tasks such as classification and regression.
Machine Learning Algorithms
Supervised Learning Algorithms
Supervised learning algorithms are powerful tools for real-world applications like fraud detection, medical diagnosis, and predictive analytics.
Unsupervised and Reinforcement Learning Algorithms
Unlike supervised learning, unsupervised learning deals with unlabeled data, meaning the algorithm must find hidden structures and patterns without predefined outputs. This approach is widely used in clustering, anomaly detection, and dimensionality reduction.