CHAPTER 1. INTRODUCTION Visible layer (input pixels) 1st hidden layer (edges) 2nd hidden layer (corners and contours) 3rd hidden layer (object parts) CAR PERSON ANIMAL Output (object identity) Figure 1.2: Illustration of a deep learning model. It is difficult for a computer to understand the meaning of raw sensory input data, such as this image represented as a collection of pixel values. The function mapping from a set of pixels to an object identity is very complicated. Learning or evaluating this mapping seems insurmountable if tackled directly. Deep learning resolves this difficulty by breaking the desired complicated mapping into a series of nested simple mappings, each described by a different layer of the model. T
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- owner: neo94 - (no access) - Ian Goodfellow, Yoshua Bengio, Aaron Courville - Deep Learning (2017, MIT).pdf, p21
- owner: dsahkjL - (no access) - Kami Export - [4]chapter-1-introduction.pdf.pdf, p6
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