rjchern

rjchern's Stars

• apache/brpc

  brpc is an Industrial-grade RPC framework using C++ Language, which is often used in high performance system such as Search, Storage, Machine learning, Advertisement, Recommendation etc. "brpc" means "better RPC".

  Language:C++16.3k4k

• mlsys-mbs0221/Multitask-Learning

  Awesome Multitask Learning Resources

  635142

• jaywcjlove/awesome-mac

   Now we have become very big, Different from the original idea. Collect premium software in various categories.

  Language:JavaScript74.4k6.2k

• Captain1986/CaptainBlackboard

  船长关于机器学习、计算机视觉和工程技术的总结和分享

  Language:C++1.2k193

• algorithm-visualizer/algorithm-visualizer

  :fireworks:Interactive Online Platform that Visualizes Algorithms from Code

  Language:JavaScript46.5k7.3k

• chatopera/Synonyms

  :herb: 中文近义词：聊天机器人，智能问答工具包

  Language:Python5k903

• mesolitica/NLP-Models-Tensorflow

  Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0

  Language:Jupyter Notebook1.8k729

• zhengyima/kg-baseline-pytorch

  2019百度的关系抽取比赛，使用Pytorch实现苏神的模型，F1在dev集可达到0.75，联合关系抽取，Joint Relation Extraction.

  Language:Python31456

• buppt/ChineseNER

  中文命名实体识别，实体抽取，tensorflow，pytorch，BiLSTM+CRF

  Language:Python1.4k396

• Wangpeiyi9979/InformationExtractionDemo

  一个关于百度2019语言与智能技术竞赛信息抽取 (http://lic2019.ccf.org.cn/kg) 的简单Demo， 模型采用BERT+CNN ( https://github.com/Wangpeiyi9979/IE-Bert-CNN )。 Demo使用Flask搭建

  Language:Python12630

• zhpmatrix/nlp-competitions-list-review

  复盘所有NLP比赛的TOP方案，只关注NLP比赛，持续更新中！

  2.6k416

• smilelight/lightNLP

  基于Pytorch和torchtext的自然语言处理深度学习框架。

  Language:Python821212

• crownpku/Information-Extraction-Chinese

  Chinese Named Entity Recognition with IDCNN/biLSTM+CRF, and Relation Extraction with biGRU+2ATT 中文实体识别与关系提取

  Language:Python2.2k814

• zenorocha/alfred-workflows

  :metal: A collection of Alfred 3 and 4 workflows that will rock your world

  12.3k851

• ShomyLiu/pytorch-relation-extraction

  distant supervised relation extraction models: PCNN MIL (Zeng 2015), PCNN+ATT(Lin 2016). 关系抽取

  Language:Python497118

• nlpAThits/figet-hyperbolic-space

  Code for the paper "Fine-Grained Entity Typing in Hyperbolic Space"

  Language:Python351

• facebookresearch/poincare-embeddings

  PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"

  Language:Python1.7k232

• facebookresearch/fairseq

  Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

  Language:Python30.1k6.4k

• ownthink/KnowledgeGraphData

  史上最大规模1.4亿中文知识图谱开源下载

  Language:Python4.9k723

• MisterBooo/LeetCodeAnimation

  Demonstrate all the questions on LeetCode in the form of animation.（用动画的形式呈现解LeetCode题目的思路）

  Language:Java75.3k14k

• josephmisiti/awesome-machine-learning

  A curated list of awesome Machine Learning frameworks, libraries and software.

  Language:Python65.2k14.6k

• dive-into-machine-learning/dive-into-machine-learning

  Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)

  11.3k1.9k

• flairNLP/flair

  A very simple framework for state-of-the-art Natural Language Processing (NLP)

  Language:Python13.8k2.1k

• ddbourgin/numpy-ml

  Machine learning, in numpy

  Language:Python15.2k3.7k

• eastlakeside/interpy-zh

  📘《Python进阶》（Intermediate Python - Chinese Version）

  Language:CSS6.5k1.3k

• NLP-LOVE/ML-NLP

  此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

  Language:Jupyter Notebook15.7k4.5k

• wangzheng0822/algo

  数据结构和算法必知必会的50个代码实现

  Language:Python22.8k7.1k

• brightmart/albert_zh

  A LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS, 海量中文预训练ALBERT模型

  Language:Python3.9k756

• thunlp/OpenKE

  An Open-Source Package for Knowledge Embedding (KE)

  Language:Python3.8k985

• dav/word2vec

  This tool provides an efficient implementation of the continuous bag-of-words and skip-gram architectures for computing vector representations of words. These representations can be subsequently used in many natural language processing applications and for further research.

  Language:C1.6k617