Name: CTO国龙剑桥博士哈牛桥智能科技CEO于红红哈佛博士
Type: User
Company: HOC Intelligent Technology哈牛桥智能科技,NTTDATAGROUP,阿里
Bio: 哈牛桥智能科技南京公司在南京江北新区软件园阿里集团NTTDATAGROUP合作
AI,IoT,RPA, OCR-AI ,ERP,cloud,bigdata,blockchain,ICT,5G,3D,AR, VR,iCLIP,核心工业软件,核心算法,中微子,顶尖前沿科技。
Location: JAPAN
Blog: https://www.oxhabridge.com
CTO国龙剑桥博士哈牛桥智能科技CEO于红红哈佛博士's Projects
Core Jupyter functionality
A tool for testing Jupyter kernels
A distributed publish/subscribe messaging service
Mirror of Apache Kafka
A tool for managing Apache Kafka.
Confluent REST Proxy for Kafka
Demo applications and code examples for Apache Kafka's Streams API.
Public Kaggle Code and Info
Predict a purchased policy based on transaction history.
Amazon access control challenge
my public kaggle code
Official Kaggle API
Code for reproducing 2nd place solution for Kaggle competition IEEE's Signal Processing Society - Camera Model Identification
Code for Kaggle EEG Detection competition
Tiny and fast effects compositor on WebGL
Web-Services Testing Made Simple
Deep Learning for humans
Keras implementations of Generative Adversarial Networks.
Run Keras models in the browser, with GPU support using WebGL
An implementation of KFAC for TensorFlow
A lightweight, pure-Swift library for downloading and caching images from the web.
The Kotlin Programming Language
Scripting enhancements for Kotlin
Production-Grade Container Scheduling and Management
Kafka cluster as Kubernetes StatefulSet, plain manifests and config
Kubernetes spawner for JupyterHub
for self-publishing
Serverless Reference Architecture for Real-time File Processing
The Image Moderator Chatbot serverless reference architecture demonstrates how to leverage Amazon Rekognition's image moderation deep learning feature to automatically remove messages containing explicit or suggestive images from channels of popular chat apps using Amazon API Gateway, AWS Lambda, and Amazon Rekognition.
The Image Recognition and Processing Backend reference architecture demonstrates how to use AWS Step Functions to orchestrate a serverless processing workflow using AWS Lambda, Amazon S3, Amazon DynamoDB and Amazon Rekognition.