Stars
Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
Library for fast text representation and classification.
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
这是一个用SpringBoot+JPA打造的基于微信服务号平台的点餐系统的后端，前端是一个使用Vue.js构建的运行于微信公众号的WebApp。前后端完全分离，前后端之间通过RESTful风格的接口相连。
微信开发 Java SDK ，支持包括微信支付，开放平台，小程序，企业微信，视频号，公众号等的后端开发
微信小程序组件 / API / 云开发示例
NideShop：基于Node.js+MySQL开发的开源微信小程序商城（微信小程序）
The world's simplest facial recognition api for Python and the command line
dl4j 基础教程 配套视频：https://space.bilibili.com/327018681/#/
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running mat…
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials,…
FastDFS is a high performance distributed file system (DFS). It's major functions include: file storing, file syncing and file accessing, and design for high capacity and load balance. Wechat/Weixi…
🎉 A curated list of awesome things related to Vue.js
Large single page application with 45 pages built on vue2 + vuex. 基于 vue2 + vuex 构建一个具有 45 个页面的大型单页面应用
spring cloud + vue + oAuth2.0全家桶实战，前后端分离模拟商城，完整的购物流程、后端运营平台，可以实现快速搭建企业级微服务项目。支持微信登录等三方登录。
Integration with Netflix OSS components
Microservice Architecture with Spring Boot, Spring Cloud and Docker
Reliable messages resolve distributed transactions
🎉 A magical vue admin https://panjiachen.github.io/vue-element-admin
My blogs and code for machine learning. http://cnblogs.com/pinard