Regularization & Optimization
Regularization prevents overfitting by penalizing model complexity, while advanced optimizers like AdamW and learning rate schedules improve convergence and generalization in neural network training.
#cs231n
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Image Classification with Linear Classifiers
Linear classifiers use learned weight matrices and biases to assign class scores, enabling fast inference but only handling linearly separable data.