Data Sparsity

Data sparsity refers to the issue of having too few data points to effectively train or fine-tune a model. Think of it like trying to learn a new language from a dictionary with only a handful of words - you'll struggle to understand context and nuances. In AI, sparse data can lead to poor model performance, making it essential to identify and address this problem through techniques like data augmentation or transfer learning.