Topic Answers Author Views
Welcome 0 Manning 552
Where's the appendix to install? 1 mythicalprogrammer 152
Section 6.1.2 Word Embeddings 0 JWG 30
Section 6.1 page 167: Set vs Multiset 0 JWG 11
Chapters 2 & 3 notes 7 timi 825
Figure 4.7 Effect of L2 weight regularization on validation loss 0 JWG 33
Some fixes for V6 10 Grigory Sapunov 109
Section 3.5.7, Listing 3.50 0 JWG 41
Question about the 7x7 window in 5.1.2 0 graki 48
Questions about 3.5.6 0 509939 48
Distributed Training for large dataset 4 203561 261
Listing 2.7 has wrong statements? 0 305903 53
The font size of the code listings in the Epub version is too small and doesn't change 0 305903 55
Chapter 7 (v6) - Listings 7.6, 7.8 1 500454 73
Depthwise separable convolution number of trainable parameters - Fig 7.16 (v6) 1 renschler 59
ModelCheckpoint and EarlyStopping Callback Question - Listing 7.20 (v6) 0 renschler 39
Typo in intro 1 511907 53
Add another figure to Bidirectional RNNs Explanation 6.3.8 (v6) 0 renschler 49
Recurrent Dropout Explanation section 6.3.6 (v6) 0 renschler 56
Two minor comments in sections 1.3.4 and 3.3.1 1 ivenzor 198
2.2.2 Vectors Discussion - Things that are confusing - Rank (v6) 0 renschler 87
Listing 3.40 and Figure 3.10 ylabel mistake (v6) 0 renschler 54
Figure 3.9 title should be "loss" not "accuracy" (v6) 0 renschler 58
Figure 3.8 and Listing 3.23 ylabel mistakes (v6) 0 renschler 53
Figure 2.5 mistake (v6) 0 renschler 52
Misleading labels in description of broadcasting, sec 2.3.2 (MEAP v6) 0 25765 64
Listing 5.31 code error 2 444147 271
Listing 5.9 += os.path.exists() 0 svenproppert 60
Some error in Figure 5.15 and 5.16 2 508012 129
Chapter 3.6 - Why does batch_size change in final model? 0 svenproppert 59
Getting an error while importing imdb dataset 2 Shuyib 174
Listing 6.8. Processing the labels of the raw IMDB data 0 244679 84
Early Stopping 0 478941 82
Typo error in chapter 5 0 508012 79
Sourcecode available? 11 256688 1003
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 82
plot 5.27 unable to reproduce the graph 0 mythicalprogrammer 88
Listing 5.20 what's the point of reshaping to (1, 150, 150, 3)? 0 mythicalprogrammer 77
Improve code in listing 2.21 0 504397 100
Reinforcement learning examples 0 Shuyib 108
Chapter 3 Model compiling 0 evohnave 96
SSE4 and AVX TensorFlow Warnings 0 evohnave 131
Google cloud deep learning instances 0 Yaakov Belch 123
Top verses Bottom of a network 0 361604 98
Adding Dropout: layer position in model 0 ythyth 141
Listing 4.9 Dropout Implementation 0 ythyth 117
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 200
Adding a densely-connected classifier on top of the convolutional base produces crazy results 6 30904 407
Grammar 0 361604 107
Listing 5.14 0 273214 99
Figure 5.12 0 273214 82
Figures 5.15 and 5.16 1 100030 164
Comment in Section 1.2.5 0 481306 75
Flatten layer 1 357482 194
typo 2.3.2 0 479823 113
listing 2.8 Training the network 0 185035 103
font size code 0 Sven Meyer 87
Multi-label classification example 1 Joey 194
schedule for publishing next chapters 1 Vaibhav Aparimit 169
Typo 5.2.4 0 Benjamin Devèze 117
Errors in drop out code 0 Benjamin Devèze 107
Errors listing 4.1 Hold-out validation 0 Benjamin Devèze 96
Typo chapter 5 1 Michael S. 161
how to explain the param statistic shown in Listing5.4 1 458045 179
AttributeError: 'NpzFile' object has no attribute 'zip' 3 456712 537
Running docker 4 4959 251
Section 2.4 1 55968 276
Listing 2.33 A naive implementation of matrix-vector dot 2 468838 205
nb_epoch renamed to epochs 0 hettlage 177
Fixed Code Listings 7 58690 487
Figure 1.2 - A new programming paradigm 0 pietz 175
Image Segmentation 1 345675 233
Section 4.5.1 (Regularisation) 0 465682 157
boston_housing is not part of keras datasets 1 favetelinguis 463
Matrix multiplication errors in Chapter 2 0 d-man 196
Listings 2.25/26 (etc.?): Naive implementations are destructive 0 noodlefrenzy 297
Shape of tweet encoding 0 hettlage 245
Incorrect formula 0 Leonard Schellenberg 322
--Deleted-- 0 timi 258