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《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。

Learn how to develop, deploy and iterate on production-grade ML applications.

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 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

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

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

Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.

🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org

🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

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

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

Topic Modelling for Humans

Oxford Deep NLP 2017 course

Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.

Natural Language Processing Tutorial for Deep Learning Researchers

A PyTorch implementation of the Transformer model in "Attention is All You Need".

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

深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）

A collection of machine learning examples and tutorials.

Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

A large-scale 7B pretraining language model developed by BaiChuan-Inc.

Pretrained model hub for Keras 3.