This repository offers structured code and notebooks to help practitioners implement few-shot learning methods, which train models to recognize new classes from only a small number of examples. It includes implementations of popular few-shot approaches with clear explanations, built on PyTorch for deep learning workflows. The focus is on making meta-learning and few-shot classification techniques accessible without navigating complex or undocumented codebases.