YUN886

YUN886's Stars

• LC044/WeChatMsg

  提取微信聊天记录，将其导出成HTML、Word、Excel文档永久保存，对聊天记录进行分析生成年度聊天报告，用聊天数据训练专属于个人的AI聊天助手

  Language:Python33.6k3.5k

• wangshusen/RecommenderSystem

  2.3k346

• JushBJJ/Mr.-Ranedeer-AI-Tutor

  A GPT-4 AI Tutor Prompt for customizable personalized learning experiences.

  28.6k3.3k

• BangLiu/ACS-QG

  Language:Python7519

• liyuanfang/mhqg

  Source code and dataset for "Difficulty-controllable Multi-hop Question Generation From Knowledge Graphs"

  Language:Python6216

• maywzh/ji_coursenotes

  Assignments and Notes for JI Courses

  Language:Jupyter Notebook54

• Greedddd/Axure

  个人设计项目“墨涧阅读”产品原型

  185

• gauthierdmn/question_generation

  Neural Question Generation using the SQuAD and NewsQA datasets

  Language:Python10837

• Maluuba/newsqa

  Tools for using Maluuba's NewsQA Dataset (public version)

  Language:Python25259

• NLP-LOVE/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。

  Language:Jupyter Notebook15.8k4.5k

• datawhalechina/leedl-tutorial

  《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

  Language:Jupyter Notebook13.3k2.9k

• fengdu78/WZU-machine-learning-course

  温州大学《机器学习》课程资料（代码、课件等）

  Language:Jupyter Notebook1.8k684

• LooperXX/CS224n-Reading-Notes

  CS224n Reading Notes in Chinese 中文阅读笔记

  492114

• tangyudi/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

  9.6k2.2k

• xiaoqian19940510/Event-Extraction

  近年来事件抽取方法总结，包括中文事件抽取、开放域事件抽取、事件数据生成、跨语言事件抽取、小样本事件抽取、零样本事件抽取等类型，DMCNN、FramNet、DLRNN、DBRNN、GCN、DAG-GRU、JMEE、PLMEE等方法

  Language:Python762134

• PaddlePaddle/PaddleNLP

  👑 Easy-to-use and powerful NLP and LLM library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.

  Language:Python12k2.9k