Supervised Learning Techniques: Background Supervised learning is a machine learning technique where a model learns from labeled data. Since every data input is paired with a corresponding output label, the model can iteratively test various weights and optimize those weights using the known ‘correct’ prediction. This allows the model to pull out complicated patterns from historical data with the goal of predicting the output for new, unseen data.
Contrast this with unsupervised learning where the model uses unlabeled data to find patterns without explicit guidance.
