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4 results for “regularisation”
Batch Normalisation
Batch normalisation is a deep learning technique that normalises the activations of each layer within a mini-batch to accelerate training and improve model stability.
Data Augmentation
A set of techniques that expand a training dataset by creating modified copies of existing examples, helping deep learning models generalise better and reducing overfitting.
Dropout
A regularisation technique in deep learning that randomly deactivates neurons during training, preventing co-adaptation and improving generalisation. Introduced by Hinton and colleagues in 2012 and formalised in 2014.
Regularisation (Machine Learning)
Regularisation is a collection of techniques in machine learning that constrain models during training to reduce overfitting and improve generalisation to unseen data.