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Updated
Jul 30, 2020 - Python
Natural language processing (NLP) is a field of computer science that studies how computers and humans interact. In the 1950s, Alan Turing published an article that proposed a measure of intelligence, now called the Turing test. More modern techniques, such as deep learning, have produced results in the fields of language modeling, parsing, and natural-language tasks.
AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
TensorFlow code and pre-trained models for BERT
中文分词 词性标注 命名实体识别 依存句法分析 语义依存分析 新词发现 关键词短语提取 自动摘要 文本分类聚类 拼音简繁转换 自然语言处理
Oxford Deep NLP 2017 course
Your new Mentor for Data Science E-Learning.
Topic Modelling for Humans
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
modest natural-language processing
NLTK Source
A very simple framework for state-of-the-art Natural Language Processing (NLP)
An open-source NLP research library, built on PyTorch.
Mapping a variable-length sentence to a fixed-length vector using BERT model
Stanford CoreNLP: A Java suite of core NLP tools.
Natural Language Processing Tutorial for Deep Learning Researchers
all kinds of text classification models and more with deep learning
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。
Code for Tensorflow Machine Learning Cookbook
XLNet: Generalized Autoregressive Pretraining for Language Understanding
TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0版入门实例代码,实战教程。
大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP
Natural Language Processing Best Practices & Examples
Created by Alan Turing