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Could anyone explain to me the differences & similarities between machine learning and system identifications? Are these just two names of the same thing? In this page, they say:

Machine learning and system identification communities are faced with similar problems where one needs to construct a model from limited or noisy observations.

I've also read the early chapters of the famous book Pattern Recognition and Machine Learning by Christopher M. Bishop. So far, my conclusion is that the problem that system identification is trying to solve is a subset of what machine learning is trying to solve.

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Machine Learning: modeling for static model and dynamic model , System Identification: focus on dynamic model or dynamic process

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You answer is a bit terse, could you elaborate your answer a bit to provide more detail - for example what is the difference (if any - I'm no expert) between the machine learning dynamic modelling and the system identification dynamic modelling - or are you saying that system identification focuses only on dynamic machine learning, whereas the broad area has a static component? (Just ideas for how you could expand your answer to make it better - maybe they're not good ones) –  Luke Mathieson Mar 30 '13 at 7:26

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