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📚TheoryIntermediate

Metric Learning

Metric learning is about automatically learning a distance function so that similar items are close and dissimilar items are far in a feature space.

#metric learning#mahalanobis distance#contrastive loss+12

∑MathIntermediate

L2 Regularization (Ridge/Weight Decay)

L2 regularization (also called ridge or weight decay) adds a penalty proportional to the sum of squared weights to discourage large parameters.

#l2 regularization

Filtering by:

#feature scaling

#ridge regression

#weight decay

+12

⚙️AlgorithmIntermediate

Gradient Descent

Gradient descent is a simple, repeatable way to move downhill on a loss surface by stepping in the opposite direction of the gradient.

#gradient descent#batch gradient descent#learning rate+12