|
About the jax category
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0
|
710
|
August 11, 2023
|
|
The Base Classification Model
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1
|
1903
|
August 6, 2024
|
|
Installation
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|
1
|
1863
|
March 21, 2024
|
|
Transformers for Vision
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|
0
|
1925
|
August 14, 2023
|
|
The Transformer Architecture
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|
0
|
1883
|
August 14, 2023
|
|
Self-Attention and Positional Encoding
|
|
0
|
1935
|
August 14, 2023
|
|
Multi-Head Attention
|
|
0
|
1883
|
August 14, 2023
|
|
The Bahdanau Attention Mechanism
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|
0
|
1753
|
August 14, 2023
|
|
Attention Scoring Functions
|
|
0
|
1303
|
August 14, 2023
|
|
Attention Pooling by Similarity
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|
0
|
1575
|
August 14, 2023
|
|
Queries, Keys, and Values
|
|
0
|
1993
|
August 14, 2023
|
|
Encoder-Decoder Seq2Seq for Machine Translation
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|
0
|
1361
|
August 14, 2023
|
|
The Encoder-Decoder Architecture
|
|
0
|
1839
|
August 14, 2023
|
|
Machine Translation and the Dataset
|
|
0
|
1320
|
August 14, 2023
|
|
Bidirectional Recurrent Neural Networks
|
|
0
|
1361
|
August 14, 2023
|
|
Deep Recurrent Neural Networks
|
|
0
|
1696
|
August 14, 2023
|
|
Gated Recurrent Units (GRU)
|
|
0
|
1517
|
August 14, 2023
|
|
Long Short-Term Memory (LSTM)
|
|
0
|
1902
|
August 14, 2023
|
|
Concise Implementation of Recurrent Neural Networks
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|
0
|
1289
|
August 14, 2023
|
|
Recurrent Neural Network Implementation from Scratch
|
|
0
|
1961
|
August 14, 2023
|
|
Recurrent Neural Networks
|
|
0
|
782
|
August 14, 2023
|
|
Language Models
|
|
0
|
1387
|
August 14, 2023
|
|
Converting Raw Text into Sequence Data
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|
0
|
1395
|
August 14, 2023
|
|
Working with Sequences
|
|
0
|
1939
|
August 14, 2023
|
|
Designing Convolution Network Architectures
|
|
0
|
1385
|
August 14, 2023
|
|
Densely Connected Networks (DenseNet)
|
|
0
|
1377
|
August 14, 2023
|
|
Residual Networks (ResNet) and ResNeXt
|
|
0
|
1870
|
August 14, 2023
|
|
Batch Normalization
|
|
0
|
1580
|
August 14, 2023
|
|
Multi-Branch Networks (GoogLeNet)
|
|
0
|
1728
|
August 14, 2023
|
|
Network in Network (NiN)
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|
0
|
1453
|
August 14, 2023
|