Topic Answers Author Views
Welcome 0 Manning 542
Section 6.1.2 Word Embeddings 0 JWG 27
Section 6.1 page 167: Set vs Multiset 0 JWG 7
Chapters 2 & 3 notes 7 timi 809
Figure 4.7 Effect of L2 weight regularization on validation loss 0 JWG 30
Some fixes for V6 10 Grigory Sapunov 101
Section 3.5.7, Listing 3.50 0 JWG 38
Question about the 7x7 window in 5.1.2 0 graki 45
Questions about 3.5.6 0 509939 44
Distributed Training for large dataset 4 203561 256
Listing 2.7 has wrong statements? 0 305903 50
The font size of the code listings in the Epub version is too small and doesn't change 0 305903 54
Chapter 7 (v6) - Listings 7.6, 7.8 1 500454 71
Depthwise separable convolution number of trainable parameters - Fig 7.16 (v6) 1 renschler 54
ModelCheckpoint and EarlyStopping Callback Question - Listing 7.20 (v6) 0 renschler 38
Typo in intro 1 511907 49
Add another figure to Bidirectional RNNs Explanation 6.3.8 (v6) 0 renschler 47
Recurrent Dropout Explanation section 6.3.6 (v6) 0 renschler 51
Two minor comments in sections 1.3.4 and 3.3.1 1 ivenzor 194
2.2.2 Vectors Discussion - Things that are confusing - Rank (v6) 0 renschler 83
Listing 3.40 and Figure 3.10 ylabel mistake (v6) 0 renschler 53
Figure 3.9 title should be "loss" not "accuracy" (v6) 0 renschler 55
Figure 3.8 and Listing 3.23 ylabel mistakes (v6) 0 renschler 50
Figure 2.5 mistake (v6) 0 renschler 50
Misleading labels in description of broadcasting, sec 2.3.2 (MEAP v6) 0 25765 63
Listing 5.31 code error 2 444147 264
Listing 5.9 += os.path.exists() 0 svenproppert 59
Some error in Figure 5.15 and 5.16 2 508012 126
Chapter 3.6 - Why does batch_size change in final model? 0 svenproppert 56
Getting an error while importing imdb dataset 2 Shuyib 170
Listing 6.8. Processing the labels of the raw IMDB data 0 244679 79
Early Stopping 0 478941 80
Typo error in chapter 5 0 508012 75
Sourcecode available? 11 256688 998
Can be explained(relu(x) is simply max(x, 0).) better by adding numbering 0 ironpython 81
section 5.1.1: invariant vs equivariant 0 330772 79
plot 5.27 unable to reproduce the graph 0 mythicalprogrammer 85
Listing 5.20 what's the point of reshaping to (1, 150, 150, 3)? 0 mythicalprogrammer 76
Improve code in listing 2.21 0 504397 98
Reinforcement learning examples 0 Shuyib 106
Where's the appendix to install? 0 mythicalprogrammer 125
Chapter 3 Model compiling 0 evohnave 95
SSE4 and AVX TensorFlow Warnings 0 evohnave 124
Google cloud deep learning instances 0 Yaakov Belch 121
Top verses Bottom of a network 0 361604 97
Adding Dropout: layer position in model 0 ythyth 140
Listing 4.9 Dropout Implementation 0 ythyth 116
Listing 7.8. Functional API implementation of a three-output model 0 273214 106
Listing 7.7. Feeding data to a multi-input model 0 273214 99
Keras is now included as part of TensorFlow! 0 273214 196
Adding a densely-connected classifier on top of the convolutional base produces crazy results 6 30904 396
Grammar 0 361604 104
Listing 5.14 0 273214 99
Figure 5.12 0 273214 82
Figures 5.15 and 5.16 1 100030 163
Comment in Section 1.2.5 0 481306 75
Flatten layer 1 357482 190
typo 2.3.2 0 479823 109
listing 2.8 Training the network 0 185035 102
font size code 0 Sven Meyer 86
Multi-label classification example 1 Joey 194
schedule for publishing next chapters 1 Vaibhav Aparimit 168
Typo 5.2.4 0 Benjamin Devèze 113
Errors in drop out code 0 Benjamin Devèze 106
Errors listing 4.1 Hold-out validation 0 Benjamin Devèze 94
Typo chapter 5 1 Michael S. 159
how to explain the param statistic shown in Listing5.4 1 458045 178
AttributeError: 'NpzFile' object has no attribute 'zip' 3 456712 516
Running docker 4 4959 247
Section 2.4 1 55968 271
Listing 2.33 A naive implementation of matrix-vector dot 2 468838 200
nb_epoch renamed to epochs 0 hettlage 174
Fixed Code Listings 7 58690 482
Figure 1.2 - A new programming paradigm 0 pietz 173
Image Segmentation 1 345675 231
Section 4.5.1 (Regularisation) 0 465682 152
boston_housing is not part of keras datasets 1 favetelinguis 457
Matrix multiplication errors in Chapter 2 0 d-man 195
Listings 2.25/26 (etc.?): Naive implementations are destructive 0 noodlefrenzy 294
Shape of tweet encoding 0 hettlage 239
Incorrect formula 0 Leonard Schellenberg 320
--Deleted-- 0 timi 255