Deep Learning Illustrated: A Visual, Interactive Guide to Artificial Intelligence

Index

A

act() method, defining DQN agent, 299–300, 301

Action potential, of biological neurons, 85–86

Action(s)

deep Q-learning network theory, 290–292

DeepMind DQN and, 59

DQN agent, 298–300

Markov decision processes and, 286

reinforcement learning problems and, 55–56

Activation functions

calculus behind backpropagation, 335–336

choosing neuron type, 96

convolutional example, 164–166

Glorot distributions, 136–137

nonlinear nature of in deep learning architectures, 95

ReLU neuron, 94–95

saturated neurons, 112–113

sigmoid neuron example, 92–94

softmax layer of fast food-classifying network, 106–108

tanh neuron, 94

Activation maps

convolutional networks and, 238

in discriminator network, 267–268

Faster R-CNN, 184–185

in generator network, 269 ...