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Learning From Data


This is a concise book. It focuses on principally linear models of supervised learning. It provides important conceptual insights into machine learing and particularly the trade-off between overfitting and underfitting. It looks at this from a number of frameworks. The writing is clear. However, I was left wanting for worked examples and was disappointed that support vector machines and kernel based methods were not explored (thught they are mentioned).

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