deep-learning
Deep learning is an AI function and subset of machine learning, used for processing large amounts of complex data.
Repositories (1427)
PyTorch training/tool code for Polygon-RNN++ (CVPR 2018)
[ICCV 2019] "DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better" by Orest Kupyn, Tetiana Martyniuk, Junru Wu, Zhangyang Wang
常用的语义分割架构结构综述以及代码复现
Re-implementation of TensorFlow in pure python, with an emphasis on code understandability
GAN-based Mel-Spectrogram Inversion Network for Text-to-Speech Synthesis
Fine-tune pretrained Convolutional Neural Networks with PyTorch
Network Slimming (Pytorch) (ICCV 2017)
A Real-time Mario Kart 64 AI using ConvNets.
Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving (ICCV, 2019)
Lightweight and Scalable framework that combines mainstream algorithms of Click-Through-Rate prediction based computational DAG, philosophy of Paramet...
deeplearning.ai , By Andrew Ng, All video link
All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN
:speech_balloon: An On-Premises, Streaming Speech Recognition System
《机器学习宝典》包含：谷歌机器学习速成课程（招式）+机器学习术语表（口诀）+机器学习规则（心得）+机器学习中的常识性问题 （内功）。该资源适用于机器学习、...
Light-Weight RefineNet for Real-Time Semantic Segmentation
Summary of deep learning models for dialog systems (Tiancheng Zhao LTI, CMU)
torchbearer: A model fitting library for PyTorch
The Implementation of FastSpeech based on pytorch.
A multi-model machine learning feature embedding database
Visual Question Answering in Pytorch
Temporary home for fastai v2 while it's being developed
Resources, datasets, papers on Question Answering
Kaggle datascience bowl 2017
Distributed Deep Learning, with a focus on distributed training, using Keras and Apache Spark.
A scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinforcement Learning.
Use PyTorch to implement some classic frameworks
Pre-trained models, data, code & materials from the paper "ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy a...