| farizrahman4u/seq2seq |
3,118 |
|
0 |
0 |
over 3 years ago |
0 |
|
105 |
gpl-2.0 |
Python |
| Sequence to Sequence Learning with Keras |
| thushv89/attention_keras |
429 |
|
0 |
0 |
about 3 years ago |
0 |
|
11 |
mit |
Python |
| Keras Layer implementation of Attention for Sequential models |
| CyberZHG/keras-transformer |
312 |
|
13 |
3 |
about 4 years ago |
39 |
January 22, 2022 |
0 |
mit |
Python |
| Transformer implemented in Keras |
| jacoxu/encoder_decoder |
256 |
|
0 |
0 |
almost 9 years ago |
0 |
|
1 |
|
Python |
| Four styles of encoder decoder model by Python, Theano, Keras and Seq2Seq |
| snatch59/keras-autoencoders |
90 |
|
0 |
0 |
about 8 years ago |
0 |
|
0 |
apache-2.0 |
Python |
| Autoencoders in Keras |
| chaitanya100100/VAE-for-Image-Generation |
75 |
|
0 |
0 |
over 7 years ago |
0 |
|
1 |
mit |
Python |
| Implemented Variational Autoencoder generative model in Keras for image generation and its latent space visualization on MNIST and CIFAR10 datasets |
| 0bserver07/Keras-SegNet-Basic |
73 |
|
0 |
0 |
over 9 years ago |
0 |
|
4 |
mit |
Jupyter Notebook |
| SegNet-Basic with Keras |
| OValery16/swap-face |
61 |
|
0 |
0 |
about 8 years ago |
0 |
|
3 |
mpl-2.0 |
Jupyter Notebook |
| Tutorial about the swap-face algorithm |
| DeepsMoseli/Bidirectiona-LSTM-for-text-summarization- |
49 |
|
0 |
0 |
over 7 years ago |
0 |
|
6 |
mit |
Python |
| A bidirectional encoder-decoder LSTM neural network is trained for text summarization on the cnn/dailymail dataset. (MIT808 project) |
| sekharvth/simple-chatbot-keras |
27 |
|
0 |
0 |
about 8 years ago |
0 |
|
0 |
mit |
Python |
| Design and build a chatbot using data from the Cornell Movie Dialogues corpus, using Keras |
