Learning Rate
Learning rate is a training hyperparameter that controls how much an AI model changes its weights during each optimization update.
#Hyperparameter
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Weight Decay
Weight decay is a regularization method that limits large model weights during training to reduce overfitting and improve generalization.
Batch Size
Batch size is the number of examples a machine learning model processes before updating its weights during training and gradient optimization.
Hyperparameter
By
AIstify Team
• 1 min read
A preset configuration that determines how a machine learning model learns from data. Adjusting hyperparameters like learning rate and depth helps optimize performance and model accuracy.