Incremental learning

Incremental learning is a machine learning paradigm where the model is trained continuously as new data arrives, rather than being trained on a fixed dataset all at once. This approach allows the system to learn from new information in a manner that is efficient and presents a number of advantages, such as: 1. **Adaptability**: The model can adapt to changes in the environment or data distribution over time without needing to be retrained from scratch.