|
About the jax category
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|
0
|
716
|
August 11, 2023
|
|
The Base Classification Model
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|
1
|
1917
|
August 6, 2024
|
|
Installation
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|
1
|
1879
|
March 21, 2024
|
|
Transformers for Vision
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|
0
|
1939
|
August 14, 2023
|
|
The Transformer Architecture
|
|
0
|
1903
|
August 14, 2023
|
|
Self-Attention and Positional Encoding
|
|
0
|
1950
|
August 14, 2023
|
|
Multi-Head Attention
|
|
0
|
1896
|
August 14, 2023
|
|
The Bahdanau Attention Mechanism
|
|
0
|
1771
|
August 14, 2023
|
|
Attention Scoring Functions
|
|
0
|
1320
|
August 14, 2023
|
|
Attention Pooling by Similarity
|
|
0
|
1598
|
August 14, 2023
|
|
Queries, Keys, and Values
|
|
0
|
2009
|
August 14, 2023
|
|
Encoder-Decoder Seq2Seq for Machine Translation
|
|
0
|
1373
|
August 14, 2023
|
|
The Encoder-Decoder Architecture
|
|
0
|
1848
|
August 14, 2023
|
|
Machine Translation and the Dataset
|
|
0
|
1335
|
August 14, 2023
|
|
Bidirectional Recurrent Neural Networks
|
|
0
|
1380
|
August 14, 2023
|
|
Deep Recurrent Neural Networks
|
|
0
|
1714
|
August 14, 2023
|
|
Gated Recurrent Units (GRU)
|
|
0
|
1535
|
August 14, 2023
|
|
Long Short-Term Memory (LSTM)
|
|
0
|
1911
|
August 14, 2023
|
|
Concise Implementation of Recurrent Neural Networks
|
|
0
|
1297
|
August 14, 2023
|
|
Recurrent Neural Network Implementation from Scratch
|
|
0
|
1972
|
August 14, 2023
|
|
Recurrent Neural Networks
|
|
0
|
788
|
August 14, 2023
|
|
Language Models
|
|
0
|
1406
|
August 14, 2023
|
|
Converting Raw Text into Sequence Data
|
|
0
|
1408
|
August 14, 2023
|
|
Working with Sequences
|
|
0
|
1951
|
August 14, 2023
|
|
Designing Convolution Network Architectures
|
|
0
|
1401
|
August 14, 2023
|
|
Densely Connected Networks (DenseNet)
|
|
0
|
1387
|
August 14, 2023
|
|
Residual Networks (ResNet) and ResNeXt
|
|
0
|
1886
|
August 14, 2023
|
|
Batch Normalization
|
|
0
|
1599
|
August 14, 2023
|
|
Multi-Branch Networks (GoogLeNet)
|
|
0
|
1743
|
August 14, 2023
|
|
Network in Network (NiN)
|
|
0
|
1479
|
August 14, 2023
|