|
About the jax category
|
|
0
|
776
|
August 11, 2023
|
|
The Base Classification Model
|
|
1
|
2018
|
August 6, 2024
|
|
Installation
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|
1
|
2012
|
March 21, 2024
|
|
Transformers for Vision
|
|
0
|
2057
|
August 14, 2023
|
|
The Transformer Architecture
|
|
0
|
2038
|
August 14, 2023
|
|
Self-Attention and Positional Encoding
|
|
0
|
2071
|
August 14, 2023
|
|
Multi-Head Attention
|
|
0
|
2012
|
August 14, 2023
|
|
The Bahdanau Attention Mechanism
|
|
0
|
1883
|
August 14, 2023
|
|
Attention Scoring Functions
|
|
0
|
1441
|
August 14, 2023
|
|
Attention Pooling by Similarity
|
|
0
|
1733
|
August 14, 2023
|
|
Queries, Keys, and Values
|
|
0
|
2121
|
August 14, 2023
|
|
Encoder-Decoder Seq2Seq for Machine Translation
|
|
0
|
1533
|
August 14, 2023
|
|
The Encoder-Decoder Architecture
|
|
0
|
1977
|
August 14, 2023
|
|
Machine Translation and the Dataset
|
|
0
|
1453
|
August 14, 2023
|
|
Bidirectional Recurrent Neural Networks
|
|
0
|
1510
|
August 14, 2023
|
|
Deep Recurrent Neural Networks
|
|
0
|
1852
|
August 14, 2023
|
|
Gated Recurrent Units (GRU)
|
|
0
|
1689
|
August 14, 2023
|
|
Long Short-Term Memory (LSTM)
|
|
0
|
2053
|
August 14, 2023
|
|
Concise Implementation of Recurrent Neural Networks
|
|
0
|
1416
|
August 14, 2023
|
|
Recurrent Neural Network Implementation from Scratch
|
|
0
|
2083
|
August 14, 2023
|
|
Recurrent Neural Networks
|
|
0
|
876
|
August 14, 2023
|
|
Language Models
|
|
0
|
1537
|
August 14, 2023
|
|
Converting Raw Text into Sequence Data
|
|
0
|
1523
|
August 14, 2023
|
|
Working with Sequences
|
|
0
|
2076
|
August 14, 2023
|
|
Designing Convolution Network Architectures
|
|
0
|
1518
|
August 14, 2023
|
|
Densely Connected Networks (DenseNet)
|
|
0
|
1497
|
August 14, 2023
|
|
Residual Networks (ResNet) and ResNeXt
|
|
0
|
2027
|
August 14, 2023
|
|
Batch Normalization
|
|
0
|
1732
|
August 14, 2023
|
|
Multi-Branch Networks (GoogLeNet)
|
|
0
|
1887
|
August 14, 2023
|
|
Network in Network (NiN)
|
|
0
|
1581
|
August 14, 2023
|