|
Concise Implementation of Softmax Regression
|
|
0
|
1312
|
June 17, 2020
|
|
The Base Classification Model
|
|
0
|
1390
|
February 1, 2022
|
|
Synthetic Regression Data
|
|
0
|
1190
|
January 22, 2022
|
|
Generalization
|
|
0
|
1826
|
June 13, 2020
|
|
Object-Oriented Design for Implementation
|
|
1
|
1799
|
July 19, 2022
|
|
Pooling
|
|
4
|
1709
|
June 28, 2022
|
|
Image Classification Dataset
|
|
9
|
3117
|
June 27, 2022
|
|
Network in Network (NiN)
|
|
2
|
1243
|
March 12, 2022
|
|
Language Models
|
|
5
|
2247
|
March 6, 2022
|
|
Padding and Stride
|
|
2
|
1854
|
February 18, 2022
|
|
Attention Cues
|
|
1
|
1850
|
February 14, 2022
|
|
Residual Networks (ResNet)
|
|
5
|
1461
|
February 14, 2022
|
|
Tensorflow consistency in d2l
|
|
2
|
552
|
February 13, 2022
|
|
Dropout
|
|
4
|
2138
|
February 10, 2022
|
|
Working with Sequences
|
|
3
|
2094
|
February 9, 2022
|
|
Convolutions for Images
|
|
10
|
2370
|
January 14, 2022
|
|
Concise Implementation of Linear Regression
|
|
4
|
1674
|
January 9, 2022
|
|
Preface
|
|
2
|
2026
|
December 30, 2021
|
|
GPUs
|
|
2
|
2261
|
December 26, 2021
|
|
Weight Decay
|
|
2
|
1838
|
November 24, 2021
|
|
Concise Implementation of Multilayer Perceptron
|
|
2
|
1531
|
October 16, 2021
|
|
How to locally build the D2L package following modification
|
|
0
|
480
|
October 6, 2021
|
|
Implementation of Multilayer Perceptrons
|
|
1
|
1927
|
September 16, 2021
|
|
Bahdanau Attention
|
|
0
|
1470
|
July 30, 2021
|
|
Encoder-Decoder Architecture
|
|
0
|
1308
|
July 30, 2021
|
|
Machine Translation and the Dataset
|
|
0
|
906
|
July 30, 2021
|
|
Deep Recurrent Neural Networks
|
|
0
|
1238
|
July 30, 2021
|
|
Long Short Term Memory (LSTM)
|
|
0
|
1627
|
July 30, 2021
|
|
Gated Recurrent Units (GRU)
|
|
0
|
862
|
July 30, 2021
|
|
Text Preprocessing
|
|
0
|
567
|
July 30, 2021
|