Popular GitHub Repositories for Arabic Nlp

? Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

12 Weeks, 24 Lessons, AI for All!

中文分词 词性标注 命名实体识别 依存句法分析 成分句法分析 语义依存分析 语义角色标注 指代消解 风格转换 语义相似度 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) in Python

Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

500 AI Machine learning Deep learning Computer vision NLP Projects with code

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.

AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

? A ranked list of awesome machine learning Python libraries. Updated weekly.

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

? 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

? The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

:book: A curated list of resources dedicated to Natural Language Processing (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。

? Discover the latest machine learning / AI courses on YouTube.

Oxford Deep NLP 2017 course

Natural Language Processing Tutorial for Deep Learning Researchers

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.