|
Concise Implementation of Softmax Regression
|
|
0
|
1534
|
June 17, 2020
|
|
The Base Classification Model
|
|
0
|
1680
|
February 1, 2022
|
|
Synthetic Regression Data
|
|
0
|
1481
|
January 22, 2022
|
|
Generalization
|
|
0
|
2171
|
June 13, 2020
|
|
Object-Oriented Design for Implementation
|
|
1
|
2144
|
July 19, 2022
|
|
Pooling
|
|
4
|
1922
|
June 28, 2022
|
|
Image Classification Dataset
|
|
9
|
3453
|
June 27, 2022
|
|
Network in Network (NiN)
|
|
2
|
1471
|
March 12, 2022
|
|
Language Models
|
|
5
|
2588
|
March 6, 2022
|
|
Padding and Stride
|
|
2
|
2084
|
February 18, 2022
|
|
Attention Cues
|
|
1
|
2146
|
February 14, 2022
|
|
Residual Networks (ResNet)
|
|
5
|
1699
|
February 14, 2022
|
|
Tensorflow consistency in d2l
|
|
2
|
681
|
February 13, 2022
|
|
Dropout
|
|
4
|
2485
|
February 10, 2022
|
|
Working with Sequences
|
|
3
|
2450
|
February 9, 2022
|
|
Convolutions for Images
|
|
10
|
2714
|
January 14, 2022
|
|
Concise Implementation of Linear Regression
|
|
4
|
2073
|
January 9, 2022
|
|
Preface
|
|
2
|
2349
|
December 30, 2021
|
|
GPUs
|
|
2
|
2609
|
December 26, 2021
|
|
Weight Decay
|
|
2
|
2141
|
November 24, 2021
|
|
Concise Implementation of Multilayer Perceptron
|
|
2
|
1797
|
October 16, 2021
|
|
How to locally build the D2L package following modification
|
|
0
|
587
|
October 6, 2021
|
|
Implementation of Multilayer Perceptrons
|
|
1
|
2244
|
September 16, 2021
|
|
Bahdanau Attention
|
|
0
|
1730
|
July 30, 2021
|
|
Encoder-Decoder Architecture
|
|
0
|
1592
|
July 30, 2021
|
|
Machine Translation and the Dataset
|
|
0
|
1090
|
July 30, 2021
|
|
Deep Recurrent Neural Networks
|
|
0
|
1515
|
July 30, 2021
|
|
Long Short Term Memory (LSTM)
|
|
0
|
1934
|
July 30, 2021
|
|
Gated Recurrent Units (GRU)
|
|
0
|
1084
|
July 30, 2021
|
|
Text Preprocessing
|
|
0
|
684
|
July 30, 2021
|