Whatever the learning strategy, the overall training steps are the same. Given some training data, the network makes its predictions and receives some feedback (such as the results of a loss function), which is then used to update the network's parameters. These steps are then repeated until the network cannot be optimized further. In this section, we will detail and implement this process, from loss computation to weights optimization.
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Finland
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Greece
Argentina
Malaysia
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Netherlands
Bulgaria
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