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About the jax category
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0
|
531
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August 11, 2023
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The Base Classification Model
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1
|
1473
|
August 6, 2024
|
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Installation
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1
|
1392
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March 21, 2024
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Transformers for Vision
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0
|
1476
|
August 14, 2023
|
|
The Transformer Architecture
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0
|
1302
|
August 14, 2023
|
|
Self-Attention and Positional Encoding
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0
|
1368
|
August 14, 2023
|
|
Multi-Head Attention
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|
0
|
1483
|
August 14, 2023
|
|
The Bahdanau Attention Mechanism
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|
0
|
1300
|
August 14, 2023
|
|
Attention Scoring Functions
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|
0
|
894
|
August 14, 2023
|
|
Attention Pooling by Similarity
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|
0
|
1082
|
August 14, 2023
|
|
Queries, Keys, and Values
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|
0
|
1517
|
August 14, 2023
|
|
Encoder-Decoder Seq2Seq for Machine Translation
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|
0
|
960
|
August 14, 2023
|
|
The Encoder-Decoder Architecture
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|
0
|
1408
|
August 14, 2023
|
|
Machine Translation and the Dataset
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0
|
894
|
August 14, 2023
|
|
Bidirectional Recurrent Neural Networks
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|
0
|
972
|
August 14, 2023
|
|
Deep Recurrent Neural Networks
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|
0
|
1331
|
August 14, 2023
|
|
Gated Recurrent Units (GRU)
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|
0
|
1073
|
August 14, 2023
|
|
Long Short-Term Memory (LSTM)
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|
0
|
1395
|
August 14, 2023
|
|
Concise Implementation of Recurrent Neural Networks
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|
0
|
862
|
August 14, 2023
|
|
Recurrent Neural Network Implementation from Scratch
|
|
0
|
1498
|
August 14, 2023
|
|
Recurrent Neural Networks
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|
0
|
571
|
August 14, 2023
|
|
Language Models
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|
0
|
983
|
August 14, 2023
|
|
Converting Raw Text into Sequence Data
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|
0
|
982
|
August 14, 2023
|
|
Working with Sequences
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|
0
|
1493
|
August 14, 2023
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|
Designing Convolution Network Architectures
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|
0
|
885
|
August 14, 2023
|
|
Densely Connected Networks (DenseNet)
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|
0
|
892
|
August 14, 2023
|
|
Residual Networks (ResNet) and ResNeXt
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|
0
|
1396
|
August 14, 2023
|
|
Batch Normalization
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|
0
|
1076
|
August 14, 2023
|
|
Multi-Branch Networks (GoogLeNet)
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|
0
|
1302
|
August 14, 2023
|
|
Network in Network (NiN)
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|
0
|
1006
|
August 14, 2023
|