|
About the jax category
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|
0
|
472
|
August 11, 2023
|
|
The Base Classification Model
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|
1
|
1351
|
August 6, 2024
|
|
Installation
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|
1
|
1224
|
March 21, 2024
|
|
Transformers for Vision
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|
0
|
1347
|
August 14, 2023
|
|
The Transformer Architecture
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|
0
|
1198
|
August 14, 2023
|
|
Self-Attention and Positional Encoding
|
|
0
|
1256
|
August 14, 2023
|
|
Multi-Head Attention
|
|
0
|
1358
|
August 14, 2023
|
|
The Bahdanau Attention Mechanism
|
|
0
|
1202
|
August 14, 2023
|
|
Attention Scoring Functions
|
|
0
|
796
|
August 14, 2023
|
|
Attention Pooling by Similarity
|
|
0
|
970
|
August 14, 2023
|
|
Queries, Keys, and Values
|
|
0
|
1405
|
August 14, 2023
|
|
Encoder-Decoder Seq2Seq for Machine Translation
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|
0
|
859
|
August 14, 2023
|
|
The Encoder-Decoder Architecture
|
|
0
|
1293
|
August 14, 2023
|
|
Machine Translation and the Dataset
|
|
0
|
797
|
August 14, 2023
|
|
Bidirectional Recurrent Neural Networks
|
|
0
|
862
|
August 14, 2023
|
|
Deep Recurrent Neural Networks
|
|
0
|
1230
|
August 14, 2023
|
|
Gated Recurrent Units (GRU)
|
|
0
|
982
|
August 14, 2023
|
|
Long Short-Term Memory (LSTM)
|
|
0
|
1272
|
August 14, 2023
|
|
Concise Implementation of Recurrent Neural Networks
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|
0
|
777
|
August 14, 2023
|
|
Recurrent Neural Network Implementation from Scratch
|
|
0
|
1389
|
August 14, 2023
|
|
Recurrent Neural Networks
|
|
0
|
519
|
August 14, 2023
|
|
Language Models
|
|
0
|
860
|
August 14, 2023
|
|
Converting Raw Text into Sequence Data
|
|
0
|
891
|
August 14, 2023
|
|
Working with Sequences
|
|
0
|
1382
|
August 14, 2023
|
|
Designing Convolution Network Architectures
|
|
0
|
779
|
August 14, 2023
|
|
Densely Connected Networks (DenseNet)
|
|
0
|
781
|
August 14, 2023
|
|
Residual Networks (ResNet) and ResNeXt
|
|
0
|
1285
|
August 14, 2023
|
|
Batch Normalization
|
|
0
|
923
|
August 14, 2023
|
|
Multi-Branch Networks (GoogLeNet)
|
|
0
|
1191
|
August 14, 2023
|
|
Network in Network (NiN)
|
|
0
|
885
|
August 14, 2023
|