yorick76ee's repositories
AI-for-Security-Learning
安全场景、基于AI的安全算法和安全数据分析学习资料整理
attribute_charge
The source code of our COLING'18 paper "Few-Shot Charge Prediction with Discriminative Legal Attributes".
Awesome-Learning-with-Label-Noise
A curated list of resources for Learning with Noisy Labels
chinese-independent-developer
👩🏿💻👨🏾💻👩🏼💻👨🏽💻👩🏻💻**独立开发者项目列表 -- 分享大家都在做什么
chromego
ChromeGo 翻墙工具包
FinancialSupportForOpenSource
开源项目挣钱实用手册
GitHub-Chinese-Top-Charts
:cn: GitHub中文排行榜，帮助你发现高分优秀中文项目、更高效地吸收国人的优秀经验成果；榜单每周更新一次，敬请关注！（最近更新于10月9日，上班快乐 :tada:）
greedyCWS
Source code for an ACL2017 paper on Chinese word segmentation
Hands-on-Machine-Learning
A series of Jupyter notebooks with Chinese comment that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
hangzhou_house_knowledge
2017年买房经历总结出来的买房购房知识分享给大家，希望对大家有所帮助。买房不易，且买且珍惜。Sharing the knowledge of buy an own house that according to the experience at hangzhou in 2017 to all the people. It's not easy to buy a own house, so I hope that it would be useful to everyone.
HATT-Proto
Code and dataset of AAAI2019 paper Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification
NiuTensor
NiuTensor is an open-source toolkit developed by a joint team from NLP Lab. at Northeastern University and the NiuTrans Team. It provides tensor utilities to create and train neural networks.
nlp-beginner
NLP上手教程
NLP-progress
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
nlp-roadmap
ROADMAP(Mind Map) and KEYWORD for students those who have interest in learning NLP
numpy-ml
Machine learning, in numpy
OpenCC
A project for conversion between Traditional and Simplified Chinese
remote-working
收集整理远程工作相关的资料
superset
Apache Superset is a Data Visualization and Data Exploration Platform
tensorflow-logistics-regression
用tensorflow实现了逻辑回归算法，将sigmoid换成softmax，实现多文本分类的任务。
textflint
Text Robustness Evaluation Platform