Transfer learning is a machine learning technique where a model developed for a particular task is reused as the starting point for a model on a second task. It leverages pre-trained models that have already been trained on large datasets, which can be fine-tuned for specific applications. This method is particularly useful in fields like Bioanalytical Sciences where data collection can be expensive and time-consuming.
