Double_V's repositories
semi-supervised-GAN
There is the semi-supervised implement of 'Improved Techniques for Training GANs '
Machine-Learning-Tutorials
machine learning and deep learning tutorials, articles and other resources
BEGAN-tensorflow
python3 / Implementation of Google Brain's BEGAN in Tensorflow
DCGAN-tensorflow
A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"
DeepLearningBookQA_cn
深度学习面试问题 回答对应的DeepLearning中文版页码
keras-dcgan
Keras implementation of Deep Convolutional Generative Adversarial Networks
lihang_book_algorithm
致力于将李航博士《统计学习方法》一书中所有算法实现一遍
Classification_Nets
Implement popular models by different DL framework. Such as tensorflow and caffe
Tensorboard
use the tensorboard freely in pytorch and keras
AdvSemiSeg
Pytorch implementation of the paper "Adversarial Learning for Semi-supervised Semantic Segmentation," Wei-Chih Hung, Yi-Hsuan Tsai, Yan-Ting Liou, Yen-Yu Lin, and Ming-Hsuan Yang
awesome-object-detection
Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html
cnn_finetune
Fine-tune CNN in Keras
DeepLearningFrameworks
Demo of running NNs across different frameworks
FaderNetworks
Fader Networks: Manipulating Images by Sliding Attributes - NIPS 2017
imgaug
Image augmentation for machine learning experiments.
magenta
Magenta: Music and Art Generation with Machine Intelligence
markdown-here
Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.
Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
Multi-label-Image-Classification
The codes for multi-label image classification
pytorch-generative-model-collections
Collection of generative models in Pytorch version.
SiamFC-PyTorch
SiamFC PyTorch
tencent-ml-images
Largest multi-label image database; ResNet-101 model; 80.73% top-1 acc on ImageNet
weightnorm
Example code for Weight Normalization, from "Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks"