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Introduction to Neural Networks - Lecture 5
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- 1 Intro
- 2 Our goal in object classification
- 3 Pixel-based representation
- 4 What we want
- 5 Some feature representations
- 6 Image classification - ImageNet
- 7 Features
- 8 Recognition task and supervision
- 9 Spectrum of supervision
- 10 The machine learning framework
- 11 Neurons in the Brain
- 12 Background in Neural Nets (NN)
- 13 Brain is a remarkable Computer
- 14 Computational Implementation of the Neural Activation Function
- 15 Binary classifying an image
- 16 Neural Networks - multiclass
- 17 Bias convenience
- 18 Composition
- 19 Problem 1 with all linear functions
