|
About the jax category
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|
0
|
491
|
August 11, 2023
|
|
The Base Classification Model
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|
1
|
1383
|
August 6, 2024
|
|
Installation
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|
1
|
1265
|
March 21, 2024
|
|
Transformers for Vision
|
|
0
|
1378
|
August 14, 2023
|
|
The Transformer Architecture
|
|
0
|
1230
|
August 14, 2023
|
|
Self-Attention and Positional Encoding
|
|
0
|
1284
|
August 14, 2023
|
|
Multi-Head Attention
|
|
0
|
1393
|
August 14, 2023
|
|
The Bahdanau Attention Mechanism
|
|
0
|
1229
|
August 14, 2023
|
|
Attention Scoring Functions
|
|
0
|
818
|
August 14, 2023
|
|
Attention Pooling by Similarity
|
|
0
|
999
|
August 14, 2023
|
|
Queries, Keys, and Values
|
|
0
|
1434
|
August 14, 2023
|
|
Encoder-Decoder Seq2Seq for Machine Translation
|
|
0
|
888
|
August 14, 2023
|
|
The Encoder-Decoder Architecture
|
|
0
|
1320
|
August 14, 2023
|
|
Machine Translation and the Dataset
|
|
0
|
823
|
August 14, 2023
|
|
Bidirectional Recurrent Neural Networks
|
|
0
|
893
|
August 14, 2023
|
|
Deep Recurrent Neural Networks
|
|
0
|
1258
|
August 14, 2023
|
|
Gated Recurrent Units (GRU)
|
|
0
|
1009
|
August 14, 2023
|
|
Long Short-Term Memory (LSTM)
|
|
0
|
1304
|
August 14, 2023
|
|
Concise Implementation of Recurrent Neural Networks
|
|
0
|
801
|
August 14, 2023
|
|
Recurrent Neural Network Implementation from Scratch
|
|
0
|
1419
|
August 14, 2023
|
|
Recurrent Neural Networks
|
|
0
|
535
|
August 14, 2023
|
|
Language Models
|
|
0
|
901
|
August 14, 2023
|
|
Converting Raw Text into Sequence Data
|
|
0
|
914
|
August 14, 2023
|
|
Working with Sequences
|
|
0
|
1410
|
August 14, 2023
|
|
Designing Convolution Network Architectures
|
|
0
|
810
|
August 14, 2023
|
|
Densely Connected Networks (DenseNet)
|
|
0
|
808
|
August 14, 2023
|
|
Residual Networks (ResNet) and ResNeXt
|
|
0
|
1310
|
August 14, 2023
|
|
Batch Normalization
|
|
0
|
969
|
August 14, 2023
|
|
Multi-Branch Networks (GoogLeNet)
|
|
0
|
1219
|
August 14, 2023
|
|
Network in Network (NiN)
|
|
0
|
921
|
August 14, 2023
|