Supervised Vs. Unsupervised Learning: Unraveling The Different Approaches In Ai

Supervised learning is a type of Artificial Intelligence (AI) methodology where the model is trained on labeled data, with the objective of learning the mapping between inputs and desired outputs. This approach is analogous to a teacher providing examples and guiding a student toward the correct answers. On the other hand, unsupervised learning takes a more exploratory path, where the algorithm is presented with unlabeled data and its task is to uncover inherent patterns and structures. The success of supervised learning is measured by the accuracy and precision of the model’s predictions, while unsupervised learning is used to discover hidden patterns and correlations in data.