The Learning Paradigm

The learning paradigm refers to the approach or framework through which systems, especially machines or algorithms, acquire knowledge or skills. It involves defining how a model learns from data—either by identifying patterns (supervised learning), discovering structures without labels (unsupervised learning), or adapting through trial and error (reinforcement learning). Essentially, it’s the methodology guiding how a system improves its performance on tasks over time by processing information and making adjustments, similar to how humans learn from experience. This paradigm shapes the design and application of AI and machine learning solutions across various fields.