This article is part of the Deep Learning hub. Training a deep network is more than choosing an architecture. The result depends on the data, the loss function, the optimiser, the regularisation s...

This article is part of the Deep Learning content hub. Training a deep network is an engineering process. It is not only a modelling problem. You need a dataset, a model, a loss function, an opti...

This article is part of the Deep Learning hub. Neural network architectures encode assumptions about the data. Choosing an architecture is not just a matter of using the newest model. It is a desi...

This article is part of the Deep Learning content hub. Deep learning architectures are not random collections of layers. Each architecture family makes assumptions about the structure of the data ...

This article is part of the Deep Learning hub. The foundations of deep learning are not only about neural network layers. They are about how data, representations, optimisation, and evaluation int...

This article is part of the Deep Learning content hub. Deep learning is often introduced through architectures: multilayer perceptrons, convolutional networks, recurrent networks, transformers, an...

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