What is the role of hyperparameters in machine learning performance?
An example of an AI chatbot conversation about the impact of hyperparameters on model performance.
What is the role of hyperparameters in machine learning performance?
Hyperparameters are settings that govern the training process of a model. They can significantly affect performance.
Can you give me some examples of hyperparameters?
Sure! Examples include learning rate, batch size, number of epochs, and the architecture of the model.
How do I choose the right hyperparameters?
Choosing hyperparameters often involves experimentation, using techniques like grid search or random search to find optimal values.
What happens if I set hyperparameters incorrectly?
Incorrect hyperparameters can lead to underfitting or overfitting, resulting in poor model performance.
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