Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Metarec | 282 | a year ago | 4 | Python | ||||||
PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models | ||||||||||
Tensorflowdeepautoencoder | 148 | 5 years ago | 6 | Python | ||||||
MNIST Digit Classification Using Stacked Autoencoder And TensorFlow | ||||||||||
Autoencoder Tensorboard T Sne | 54 | 5 years ago | 1 | mit | Python | |||||
Plugging TensorBoard in an autoencoder on the MNIST dataset for demonstrating t-SNE embeddings visualization of unsupervised machine learning. | ||||||||||
Deep Convolutional Autoencoder | 41 | 7 years ago | 2 | Python | ||||||
This is a tutorial on creating a deep convolutional autoencoder with tensorflow. | ||||||||||
Pytorch_sac_ae | 38 | 4 years ago | mit | Python | ||||||
PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE) | ||||||||||
Tf2 Published Models | 33 | 3 years ago | 1 | apache-2.0 | Python | |||||
Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are implemented and can be seen in tensorboard. | ||||||||||
F Anogan_with_pytorch | 20 | 4 years ago | 1 | Jupyter Notebook | ||||||
Aiqn Vae | 9 | 5 years ago | mit | Python | ||||||
VAE + Quantile Networks for MNIST | ||||||||||
Restricted Boltzmann Machines | 7 | 4 years ago | Jupyter Notebook | |||||||
Implementation of restricted Boltzmann machines in Tensorflow 2 | ||||||||||
V2a | 5 | 4 years ago | Python | |||||||
Autoencoding visual-to-auditory sensory substitution |