Training-serving skew: Difference between revisions

Training-serving skew (view source)

443 bytes removed , 25 February 2023

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 Finally, it is essential to carefully manage both training and deployment environments in order to create a consistent experience. This may involve using similar hardware configurations, software dependencies, and data distributions across both environments.
-==Explain Like I'm 5 (ELI5)==
-Training-serving skew occurs when a computer program (known as a machine learning model) behaves differently during testing than it does during actual usage. This can occur due to differences in data, the computer it's running on, or the tools it utilizes. To resolve this issue, people can ensure the testing and using conditions are similar or test the program under various scenarios to observe its behavior.
 ==Explain Like I'm 5 (ELI5)==