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The use of normalisation in neural networks and many other (but not all - decision trees are a notable exception) machine learning methods, is to improve the quality of the parameter space with respect to optimisers that will apply to it. If you are using a function approximator that benefits from normalisation in supervised learning scenarios, it will also ...

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