Optimization
The process of adjusting model parameters to minimize loss and improve performance.
In more detail
Optimization algorithms include SGD, Adam, RMSprop, and others. They update weights based on gradients computed via backpropagation. Key hyperparameters include learning rate and batch size. Proper optimization is crucial for model convergence and performance.
Examples
- Gradient Descent
- Adam Optimizer
- RMSprop
- Learning rate scheduling
Related terms
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