What is batch encoding?

Batch encoding refers to the process of encoding multiple data samples simultaneously rather than individually. This technique is commonly used in machine learning and data processing to improve efficiency, as it allows for parallel processing and reduces the overhead associated with handling each sample separately. In contexts such as natural language processing or image processing, batch encoding can enhance performance and speed when training models. Overall, it optimizes resource utilization and can lead to better model training outcomes.