|
About the jax category
|
|
0
|
466
|
August 11, 2023
|
|
The Base Classification Model
|
|
1
|
1342
|
August 6, 2024
|
|
Installation
|
|
1
|
1212
|
March 21, 2024
|
|
Transformers for Vision
|
|
0
|
1339
|
August 14, 2023
|
|
The Transformer Architecture
|
|
0
|
1189
|
August 14, 2023
|
|
Self-Attention and Positional Encoding
|
|
0
|
1245
|
August 14, 2023
|
|
Multi-Head Attention
|
|
0
|
1348
|
August 14, 2023
|
|
The Bahdanau Attention Mechanism
|
|
0
|
1191
|
August 14, 2023
|
|
Attention Scoring Functions
|
|
0
|
784
|
August 14, 2023
|
|
Attention Pooling by Similarity
|
|
0
|
961
|
August 14, 2023
|
|
Queries, Keys, and Values
|
|
0
|
1394
|
August 14, 2023
|
|
Encoder-Decoder Seq2Seq for Machine Translation
|
|
0
|
853
|
August 14, 2023
|
|
The Encoder-Decoder Architecture
|
|
0
|
1272
|
August 14, 2023
|
|
Machine Translation and the Dataset
|
|
0
|
788
|
August 14, 2023
|
|
Bidirectional Recurrent Neural Networks
|
|
0
|
853
|
August 14, 2023
|
|
Deep Recurrent Neural Networks
|
|
0
|
1221
|
August 14, 2023
|
|
Gated Recurrent Units (GRU)
|
|
0
|
973
|
August 14, 2023
|
|
Long Short-Term Memory (LSTM)
|
|
0
|
1263
|
August 14, 2023
|
|
Concise Implementation of Recurrent Neural Networks
|
|
0
|
769
|
August 14, 2023
|
|
Recurrent Neural Network Implementation from Scratch
|
|
0
|
1378
|
August 14, 2023
|
|
Recurrent Neural Networks
|
|
0
|
513
|
August 14, 2023
|
|
Language Models
|
|
0
|
850
|
August 14, 2023
|
|
Converting Raw Text into Sequence Data
|
|
0
|
885
|
August 14, 2023
|
|
Working with Sequences
|
|
0
|
1371
|
August 14, 2023
|
|
Designing Convolution Network Architectures
|
|
0
|
772
|
August 14, 2023
|
|
Densely Connected Networks (DenseNet)
|
|
0
|
773
|
August 14, 2023
|
|
Residual Networks (ResNet) and ResNeXt
|
|
0
|
1270
|
August 14, 2023
|
|
Batch Normalization
|
|
0
|
908
|
August 14, 2023
|
|
Multi-Branch Networks (GoogLeNet)
|
|
0
|
1182
|
August 14, 2023
|
|
Network in Network (NiN)
|
|
0
|
874
|
August 14, 2023
|