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🧑🚀 全世界最好的LLM资料总结 | Summary of the world's best LLM resources.
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
SCOPE-RL: A python library for offline reinforcement learning, off-policy evaluation, and selection
just a bunch of useful embeddings for scikit-learn pipelines
为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, m…
OpenMMLab Text Detection, Recognition and Understanding Toolbox
Combining MMOCR with Segment Anything & Stable Diffusion. Automatically detect, recognize and segment text instances, with serval downstream tasks, e.g., Text Removal and Text Inpainting
Find data quality issues and clean your data in a single line of code with a Scikit-Learn compatible Transformer.
Combining Segment Anything (SAM) with Grounded DINO for zero-shot object detection and CLIPSeg for zero-shot segmentation
AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
一份通俗易懂、风趣幽默的Java学习指南，内容涵盖Java基础、Java并发编程、Java虚拟机、Java企业级开发、Java面试等核心知识点。学Java，就认准二哥的Java进阶之路😄
LibAUC: A Deep Learning Library for X-Risk Optimization
HistoQC is an open-source quality control tool for digital pathology slides
[ECCVW 2022] The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"
A library of transformer models for computer vision and multi-modality research
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
A deep learning approach to predicting breast tumor proliferation scores for the TUPAC16 challenge
Python Whole Slide Image Preprocessing
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Sample code for the ASP.NET Core 3 and Angular 9 programming book
Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website (https://dlg4nlp.github.io/index.html) for various learning resources!
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。
Implementation of Statistical Learning Method, Second Edition.《统计学习方法》第二版，算法实现。
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Python Data Science Handbook: full text in Jupyter Notebooks