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

💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython

Oxford Deep NLP 2017 course

Your new Mentor for Data Science E-Learning.

📖 A curated list of resources dedicated to Natural Language Processing (NLP)

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants

This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

modest natural-language processing

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

NLTK Source

🤖 The Conversational Platform with built-in language understanding (NLU), beautiful graphical interface and Dialog Manager (DM). Easily create chatbots and AI-based virtual assistants.

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

Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.

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。

all kinds of text classification models and more with deep learning

A curated list of resources for Chinese NLP 中文自然语言处理相关资料

ansj分词.ict的真正java实现.分词效果速度都超过开源版的ict. 中文分词,人名识别,词性标注,用户自定义词典

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

XLNet: Generalized Autoregressive Pretraining for Language Understanding

Natural Language Processing Best Practices & Examples