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Learning Large Language Model (LLM）(大语言模型学习)
links to conference publications in graph-based deep learning
查询东南大学九龙湖/丁家桥/无锡校区各个充电桩的可用情况
An index of algorithms for learning causality with data
A curated (most recent) list of resources for Learning with Noisy Labels
A curated list of resources for Learning with Noisy Labels
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…
Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复
ChatGPT 中文调教指南。各种场景使用指南。学习怎么让它听你的话。
This repo includes ChatGPT prompt curation to use ChatGPT and other LLM tools better.
This is the notes of the way of machine learning study. You may find something useful in it.
A Python implementation of global optimization with gaussian processes.
mPLUG-Owl: The Powerful Multi-modal Large Language Model Family
A playbook for systematically maximizing the performance of deep learning models.
An unofficial styleguide and best practices summary for PyTorch
Must-read papers on graph neural networks (GNN)
My blogs and code for machine learning. http://cnblogs.com/pinard
Some Conferences' accepted paper lists (including AI, ML, Robotic)
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
PyTorch Tutorial for Deep Learning Researchers
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
Statistical Learning Theory (CS229T) Lecture Notes
The most cited deep learning papers
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
2023年最新总结，阿里，腾讯，百度，美团，头条等技术面试题目，以及答案，专家出题人分析汇总。