What is the difference between debugging and testing in AI?
An example of an AI chatbot conversation about debugging vs testing in AI.
What is the difference between debugging and testing in AI?
Debugging is the process of identifying and fixing errors in code, while testing evaluates the performance and functionality.
Can you give me examples of each in the context of AI?
Sure! Debugging might involve fixing a neural network that isn't learning properly, while testing could involve validating model accuracy on a dataset.
How do these processes impact the development of AI models?
Both are crucial; debugging ensures the model runs correctly, while testing ensures it meets performance standards before deployment.
Are there specific tools used for debugging and testing in AI?
Yes, tools like TensorBoard for visualization and PyTest for unit testing are commonly used in AI development.
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