Setting up Knet
Installation
Tips for developers
Using Amazon AWS
Introduction to Knet
Contents
Installation
Examples
Benchmarks
Function reference
Optimization methods
Under the hood
Contributing
Backpropagation
Partial derivatives
Chain rule
Multiple dimensions
Multiple instances
Stochastic Gradient Descent
References
Softmax Classification
Classification
Likelihood
Softmax
One-hot vectors
Gradient of log likelihood
MNIST example
Representational power
References
Multilayer Perceptrons
Stacking linear classifiers is useless
Introducing nonlinearities
Types of nonlinearities (activation functions)
Representational power
Matrix vs Neuron Pictures
Programming Example
References
Convolutional Neural Networks
Motivation
Convolution
Pooling
Normalization
Architectures
Exercises
References
Recurrent Neural Networks
References
Reinforcement Learning
References
Optimization
References
Generalization
References
Knet.jl
Docs
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Index
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Index