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About the jax category
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0
|
626
|
August 11, 2023
|
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The Base Classification Model
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1
|
1690
|
August 6, 2024
|
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Installation
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|
1
|
1650
|
March 21, 2024
|
|
Transformers for Vision
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0
|
1702
|
August 14, 2023
|
|
The Transformer Architecture
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|
0
|
1600
|
August 14, 2023
|
|
Self-Attention and Positional Encoding
|
|
0
|
1670
|
August 14, 2023
|
|
Multi-Head Attention
|
|
0
|
1723
|
August 14, 2023
|
|
The Bahdanau Attention Mechanism
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|
0
|
1526
|
August 14, 2023
|
|
Attention Scoring Functions
|
|
0
|
1099
|
August 14, 2023
|
|
Attention Pooling by Similarity
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|
0
|
1315
|
August 14, 2023
|
|
Queries, Keys, and Values
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|
0
|
1750
|
August 14, 2023
|
|
Encoder-Decoder Seq2Seq for Machine Translation
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|
0
|
1168
|
August 14, 2023
|
|
The Encoder-Decoder Architecture
|
|
0
|
1628
|
August 14, 2023
|
|
Machine Translation and the Dataset
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|
0
|
1098
|
August 14, 2023
|
|
Bidirectional Recurrent Neural Networks
|
|
0
|
1193
|
August 14, 2023
|
|
Deep Recurrent Neural Networks
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|
0
|
1529
|
August 14, 2023
|
|
Gated Recurrent Units (GRU)
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|
0
|
1290
|
August 14, 2023
|
|
Long Short-Term Memory (LSTM)
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|
0
|
1625
|
August 14, 2023
|
|
Concise Implementation of Recurrent Neural Networks
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|
0
|
1083
|
August 14, 2023
|
|
Recurrent Neural Network Implementation from Scratch
|
|
0
|
1724
|
August 14, 2023
|
|
Recurrent Neural Networks
|
|
0
|
689
|
August 14, 2023
|
|
Language Models
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|
0
|
1204
|
August 14, 2023
|
|
Converting Raw Text into Sequence Data
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|
0
|
1189
|
August 14, 2023
|
|
Working with Sequences
|
|
0
|
1706
|
August 14, 2023
|
|
Designing Convolution Network Architectures
|
|
0
|
1089
|
August 14, 2023
|
|
Densely Connected Networks (DenseNet)
|
|
0
|
1086
|
August 14, 2023
|
|
Residual Networks (ResNet) and ResNeXt
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|
0
|
1641
|
August 14, 2023
|
|
Batch Normalization
|
|
0
|
1338
|
August 14, 2023
|
|
Multi-Branch Networks (GoogLeNet)
|
|
0
|
1525
|
August 14, 2023
|
|
Network in Network (NiN)
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|
0
|
1226
|
August 14, 2023
|