👉 Identifiability is a concept in machine learning and data science that refers to how well a model can be predicted or classified. It involves identifying which features are relevant to a particular task, so that the model can accurately predict or classify outcomes based on those features. Identifiability helps ensure that a model's predictions are as accurate and reliable as possible, leading to better performance in various applications such as computer vision, natural language processing, and other areas of machine learning.