Name: Renfei HUANG
Type: User
Bio: MPhil, CSE, HKUST.
BEng, CKC Honors College, ZJU.
Interested in Distributed Systems, Cloud Computing, Blockchain and Data Visualization, XAI.
Location: Clear Water Bay, Kowloon, Hong Kong
Blog: https://lifewinnerhuang.github.io/
Renfei HUANG's Projects
Curriculum for learning front-end development during #100DaysOfCode.
Easily create a beautiful website using Academic and Hugo
Alluxio, formerly Tachyon, Unify Data at Memory Speed
A curated list of awesome computer vision resources
A collection of research materials on explainable AI/ML
A list of recommended research papers and other readings on data visualization
:octocat:GitHub最全的前端资源汇总仓库(包括前端学习、开发资源、求职面试等)
全JavaScript语言Web项目——图书管理系统
The coding practice of HKUST VisLab which is required to be finished by each student.
Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:
互联网大厂内推及大厂面经整理,并且每天一道面试题推送。每天五分钟,半年大厂中
An open source smart contract platform
Repository for few-shot learning machine learning projects
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning, in ICCV 2021
Manually curated collection of resources for frontend web developers.
The Grammar of Graphics in JavaScript
GPL version of Javascript Gantt Chart
Gantt chart library using D3.js.
LaTex source and slides of my HKUST Mphil Thesis on "Mars: accelerating MapReduce with graphics processors"
The Hong Kong University of Science and Technology PhD/MPhil thesis latex template based on the latest official sample (http://pg.ust.hk/guides_n_forms/students/thesis_sample_page_phd.pdf)
The website designer for Hugo. Build and deploy a beautiful website in minutes :rocket:
Tutorial materials for Data Visualization course at HKUST
汇总各大互联网公司容易考察的高频leetcode题🔥 推荐刷题网站:https://www.lintcode.com/?utm_source=tf-github-codetop
MAML Implementation using Pytorch-lightning
Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)
Faster and elegant TensorFlow Implementation of paper: Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks