Renfei HUANG's repositories
Coding_Training_HKUST_VIS_2019
The coding practice of HKUST VisLab which is required to be finished by each student.
100-days-of-code-frontend
Curriculum for learning front-end development during #100DaysOfCode.
academic-kickstart
Easily create a beautiful website using Academic and Hugo
Awesome-explainable-AI
A collection of research materials on explainable AI/ML
awesome-visualization-research
A list of recommended research papers and other readings on data visualization
Awsome-Front-End-learning-resource
: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）
d3
Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:
Daily-Question
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
eos
An open source smart contract platform
few-shot
Repository for few-shot learning machine learning projects
few-shot-meta-baseline
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning, in ICCV 2021
frontend-dev-bookmarks
Manually curated collection of resources for frontend web developers.
g2
The Grammar of Graphics in JavaScript
gantt
GPL version of Javascript Gantt Chart
HKUST_PhD_MPhil_thesis_Latex
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)
hugo-academic
The website designer for Hugo. Build and deploy a beautiful website in minutes :rocket:
learning-vis-tools
Tutorial materials for Data Visualization course at HKUST
LeetcodeTop
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
lightning-maml
MAML Implementation using Pytorch-lightning
maml
Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"
MAML-Pytorch
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)
meta-dataset
A dataset of datasets for learning to learn from few examples
pdash
mirror of https://bitbucket.org/cpchain-pdash/pdash
PyTorch-MAML
A PyTorch implementation of Model Agnostic Meta-Learning (MAML) that faithfully reproduces the results from the original paper.
pytorch-meta
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
valley-beyond
失败学资料指南