Advanced Deep Learning with Keras

Actor-Critic method, advantages 317
baseline method 313
multilayer perceptron (MLP)
about 6
loss function 15, 17
MNIST dataset 6, 8
MNIST digits classifier model 8-12
model summary 22
optimization 17-19
output activation 15, 17
performance evaluation 20
regularization 14
used, for building model 12-14
N
natural language processing (NLP) 31
nondeterministic environment 287
O
one-hot vector 11
OpenAI
URL 341
P
partially observable MDP (POMDP) 273
pix2pix 203
policy gradient methods
performance evaluation 335-340
with Keras 318-332
policy gradient theorem
about 308-311
URL 310
Python
Q-learning, implementing 281, 286
Q
Q-learning
examples 276-280
implementing, in Python 281, 286
on OpenAI gym 288, 289
Q value 274, 275
R
Reconstruction Loss 241
Rectified Linear Unit (ReLU) 13, 105
Recurrent Neural Networks (RNN) 31-36
Reinforcement Learning (RL)
about 271
principles 272-274
Reparameterization Trick 243
ResNet 39
ResNet v2 59-62
ResNeXt 39
Root Mean Squared Propagation
(RMSprop) 17
S
Sequential Model API 2
Stacked Generative Adversarial Network
(StackedGAN)
about 162, 179, 180, 184
conclusion 200
Conditional loss function 184
Entropy loss function 184
Generator Outputs 197, 200
implementations, in Keras 181-193
Stochastic Gradient Descent (SGD) 17
Street View House Numbers (SVHN) 204
structural similarity index (SSIM) 73
T
target (ground truth) 6
Temporal-Difference Learning
(TD-Learning) 287
TensorFlow
installing 3, 4
reference 4
Transposed CNN (deconvolution) 78
U
U-Net 212
unsupervised learning 71
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