sjchoi86 / Advanced Tensorflow
Little More Advanced TensorFlow Implementations
Stars: â 364
Projects that are alternatives of or similar to Advanced Tensorflow
Catdcgan
A DCGAN that generate Cat pictures ðąâðŧ
Stars: â 177 (-51.37%)
Mutual labels: jupyter-notebook, gan
Swapnet
Virtual Clothing Try-on with Deep Learning. PyTorch reproduction of SwapNet by Raj et al. 2018. Now with Docker support!
Stars: â 202 (-44.51%)
Mutual labels: jupyter-notebook, gan
Keraspp
ė―ëĐė
°íė 3ëķ ëĨëŽë, ėžëžėĪë§
Stars: â 178 (-51.1%)
Mutual labels: jupyter-notebook, gan
Cartoonify
Deploy and scale serverless machine learning app - in 4 steps.
Stars: â 157 (-56.87%)
Mutual labels: jupyter-notebook, gan
Pytorch Lesson Zh
pytorch å
æäļå
äž
Stars: â 279 (-23.35%)
Mutual labels: jupyter-notebook, gan
Pix2pix Film
An implementation of Pix2Pix in Tensorflow for use with frames from films
Stars: â 162 (-55.49%)
Mutual labels: jupyter-notebook, gan
Dragan
A stable algorithm for GAN training
Stars: â 189 (-48.08%)
Mutual labels: jupyter-notebook, gan
Data science blogs
A repository to keep track of all the code that I end up writing for my blog posts.
Stars: â 139 (-61.81%)
Mutual labels: jupyter-notebook, gan
Nn
ð§âðŦ 50! Implementations/tutorials of deep learning papers with side-by-side notes ð; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), ðŪ reinforcement learning (ppo, dqn), capsnet, distillation, ... ð§
Stars: â 5,720 (+1471.43%)
Mutual labels: jupyter-notebook, gan
Gan Tutorial
Simple Implementation of many GAN models with PyTorch.
Stars: â 227 (-37.64%)
Mutual labels: jupyter-notebook, gan
Pytorch Gan
A minimal implementaion (less than 150 lines of code with visualization) of DCGAN/WGAN in PyTorch with jupyter notebooks
Stars: â 150 (-58.79%)
Mutual labels: jupyter-notebook, gan
Zhihu
This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.
Stars: â 3,307 (+808.52%)
Mutual labels: jupyter-notebook, gan
Face generator
DCGAN face generator ð§.
Stars: â 146 (-59.89%)
Mutual labels: jupyter-notebook, gan
Image generator
DCGAN image generator ðžïļ.
Stars: â 173 (-52.47%)
Mutual labels: jupyter-notebook, gan
Gans From Theory To Production
Material for the tutorial: "Deep Diving into GANs: from theory to production"
Stars: â 182 (-50%)
Mutual labels: jupyter-notebook, gan
Deep Learning With Python
Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.
Stars: â 134 (-63.19%)
Mutual labels: jupyter-notebook, gan
Generative adversarial networks 101
Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.
Stars: â 138 (-62.09%)
Mutual labels: jupyter-notebook, gan
Gan steerability
On the "steerability" of generative adversarial networks
Stars: â 225 (-38.19%)
Mutual labels: jupyter-notebook, gan
Faceswap Gan
A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.
Stars: â 3,099 (+751.37%)
Mutual labels: jupyter-notebook, gan
Advanced TensorFlow
Collection of (Little More + Refactored) Advanced TensorFlow Implementations. Try my best to implement algorithms with a single Jupyter Notebook.
AutoEncoder
- Denoising AutoEncoder
- Convolutional AutoEncoder (using deconvolution)
- Variational AutoEncoder
Adversarial Variational Bayes
- AVB on 2-dimensional Toy Example
Basics
- Basic Classification (MLP and CNN)
- Custom Dataset Generation
- Classification (MLP and CNN) using Custom Dataset
- OOP Style Implementation of MLP and CNN
Class Activation Map
- Pretrained Network Usage with TF-SLIM
- Class Activation Map with Pretrained Network
Char-RNN
- Preprocess Linux Kernel Sources
- Train and Sample with Char-RNN
Domain Adaptation
- Domain Adversarial Neural Network with Gradient Reversal Layer
Generative Adversarial Network
- Deep Convolutional Generative Adversarial Network with MNIST
Mixture Density Network
- Mixture Density Network
- Heteroscedastic Mixture Density Network
Reinforcement Learning
- Model Based RL (Value Iteration and Policy Iteration)
TF-SLIM
- MNIST Classification with TF-SLIM
Super Resolution
- Super-resolution with Generative Adversarial Network
Requirements
- Python-2.7
- TensorFlow-1.0.1
- SciPy
- MatplotLib
- Jupyter Notebook
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].