Transcription of Introduction - Deep Learning
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Introduction - Deep Learning
Introduction Lecture slides for Chapter 1 of Deep Learning Ian Goodfellow 2016-09-26. Representations Matter APTER 1. Introduction . Cartesian coordinates Polar coordinates y . x r Figure suppose we want to separate ure : Example of di erent representations: (Goodfellow 2016). Depth: Repeated Composition CHAPTER 1. Introduction . Output CAR PERSON ANIMAL. (object identity). 3rd hidden layer (object parts). 2nd hidden layer (corners and contours). 1st hidden layer (edges). Visible layer (input pixels). Figure : Illustration of a deep Learning model. It is di cult for a computer to understand Figure the meaning of raw sensory input data, such as this image represented as a collection (Goodfellow 2016).
Machine Learning and AI CHAPTER 1. INTRODUCTION AI Machine learning Representation learning Deep learning Example: Knowledge bases Example: Logistic regression Example: Shallow Example: autoencoders MLPs Figure 1.4: A Venn diagram showing how deep learning is a kind of representation learning, which is in turn a kind of machine learning, which ...
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