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neihsyin's Projects

ai-learn icon ai-learn

人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理,PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

bert-as-service icon bert-as-service

Mapping a variable-length sentence to a fixed-length vector using BERT model

causaltree icon causaltree

Working repository for Causal Tree and extensions

chinese-bert-wwm icon chinese-bert-wwm

Pre-Training with Whole Word Masking for Chinese BERT(中文BERT-wwm系列模型)

cntopic icon cntopic

简单好用的lda话题模型,支持中英文。该库基于gensim和pyLDAvis,实现了lda话题模型及可视化功能。

d2l-pytorch icon d2l-pytorch

This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.

drhur icon drhur

package for the workshops of "Learning R with Dr. Hu"

hanlp icon hanlp

Natural Language Processing for the next decade. Tokenization, Part-of-Speech Tagging, Named Entity Recognition, Syntactic & Semantic Dependency Parsing, Document Classification

interesting-python icon interesting-python

有趣的Python爬虫和Python数据分析小项目(Some interesting Python crawlers and data analysis projects)

intror icon intror

这是一本中文 R 语言入门书,基于最新 tidyverse 包。

jiebar icon jiebar

Chinese text segmentation with R. R语言中文分词 (文档已更新 🎉 :https://qinwenfeng.com/jiebaR/ )

mars icon mars

Mars is a tensor-based unified framework for large-scale data computation which scales Numpy, Pandas and Scikit-learn.

ml-nlp icon 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。

nndl.github.io icon nndl.github.io

《神经网络与深度学习》 Neural Network and Deep Learning

pyhanlp icon pyhanlp

中文分词 词性标注 命名实体识别 依存句法分析 新词发现 关键词短语提取 自动摘要 文本分类聚类 拼音简繁 自然语言处理

quanteda icon quanteda

An R package for the Quantitative Analysis of Textual Data

roberta_zh icon roberta_zh

RoBERTa中文预训练模型: RoBERTa for Chinese

top2vec icon top2vec

Top2Vec learns jointly embedded topic, document and word vectors.

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