What are some common loss functions in PyTorch?
An example of an AI chatbot conversation about PyTorch loss functions.
What are some common loss functions in PyTorch?
In PyTorch, common loss functions include Mean Squared Error (MSE), Cross Entropy Loss, and Hinge Loss. Each serves different purposes.
Can you explain how Cross Entropy Loss works?
Cross Entropy Loss measures the difference between two probability distributions: the true labels and the predicted probabilities. It's commonly used for classification tasks.
When should I use Mean Squared Error?
Mean Squared Error is typically used for regression tasks where you want to minimize the average squared difference between predicted and actual values.
Are there any other loss functions I should know about?
Yes, there are many others like Kullback-Leibler Divergence, Focal Loss, and Smooth L1 Loss, each suited for specific scenarios.
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