"Deep learning constructs internal representations of patterns that predict labels such as “cow” from large collections of training images."
The authors describe how deep networks learn hierarchical visual representations, beginning with elementary features and progressing toward combinations associated with objects. This provides a technical foundation for the book's cow-recognition example and its explanation of how image classifiers learn predictive features from training data.
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