What is prefetching in machine learning?
An example of an AI chatbot conversation about prefetching in machine learning.
What is prefetching in machine learning?
Prefetching in machine learning refers to the technique of loading data or resources in advance to improve performance.
How does prefetching improve the efficiency of machine learning models?
It reduces latency by ensuring that the necessary data is available when needed, thus speeding up training and inference.
Can you give an example of prefetching in a real-world application?
Sure! In image recognition, prefetching can load images into memory before they are processed, enhancing speed.
Are there any downsides to using prefetching?
Yes, if not managed properly, it can lead to increased memory usage and may fetch unnecessary data.
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