我的收藏
记录一下自己的收藏夹
学习资源
计算机科学
- 《深入理解计算机系统》Attack Lab实验解析 | Yi’s Blog
- xiaolincoder/CS-Base: 图解计算机网络、操作系统、计算机组成、数据库，共 1000 张图 + 50 万字，破除晦涩难懂的计算机基础知识，让天下没有难懂的八股文！
- Philosophy of software design
数据结构与算法
机器学习与深度学习
- 20天吃透Pytorch
- How to Train Really Large Models on Many GPUs? | Lil’Log
- 归档 | Breezedeus.com
- 张振虎的博客
- diffusion_model | 莫叶何竹
- 知识库精选 | Way to AGI
机器学习系统
- ML system 入坑指南 | 摸黑干活
- 从AI系统角度回顾GPU架构变迁–从Fermi到Ampere - 知乎
- 大模型Infra这些年，从黑铁时代到黄金时代再到白银时代 - 知乎
- horseee/DeepCache: [CVPR 2024] DeepCache
- Physics of Language Models - Part 1
- Contribute to vllm-project/vllm
- 手写 Self-Attention 的四重境界
- MLSys-Learner-Resources/Awesome-MLSys-Blogger
- How To Scale Your Model
- stas00/ml-engineering: Machine Learning Engineering Open Book
- HuaizhengZhang/AI-System-School
- Machine Learning Systems
- Stanford MLSys Seminar
大语言模型与RAG
- 论文精读 - 知乎
- 精通 RAG：如何构建企业 RAG 系统 - 掘金
- 一文读懂：大模型RAG（检索增强生成） - 知乎
- 当推荐系统遇见大语言模型 - 大模型知识库
- langchain-ai/rag-from-scratch
- NirDiamant/RAG_Techniques
- LLM Agents | Prompt Engineering Guide
- Thinking-Claude
- Patterns for Building LLM-based Systems & Products
在线课程与学习资源
- MIT-Missing-Semester - CS自学指南
- Courses - DeepLearning.AI
- 11-777 MMML | Schedule
- CS 194/294-267 Understanding Large Language Models | Spring 2024
- MIT 6.S978: Deep Generative Models, Fall 2024
- Introduction | CS324
- Syllabus | Large Language Model Systems
- ML 2022 Spring
- Home | CSE 234
- mryab/efficient-dl-systems
- CSE 599 — ML for ML Systems
- AI-Sys Sp22
- Lectures - dlsyscourse
- MIT 6.5940 Fall 2024 TinyML
- TinyMLedu Courses
- CSCE 585: Machine Learning Systems
- MIT 6.S965 Fall 2022 TinyML
- Mastering Markdown · GitHub Guides
面试与求职
- Interview Query | Dashboard
- CyC2018/CS-Notes: 技术面试必备基础知识
- System Design Interviews - BugFree.ai
- BQ总结1 · High Frequency Interview Questions and Answers
- SDE Interview Guide
- 胖头龙的咸鱼刷题笔记 - 一亩三分地
- datawhalechina/daily-interview
- 分享一些Jedi BQ的经验
- interview questions
- 个人经验教你如何准备MLE/AS的面试 - 一亩三分地
- Introduction to Machine Learning Interviews Book · MLIB
产品与数据分析
产品管理
- 增长黑客技能树
- 人人都是产品经理
- 更好的产品指标：在不同阶段如何使用指标
- Startup Metrics for Pirates: AARRR! | Medium
- Data-Informed Product Building | Sequoia
A/B测试
- Experiment Design - norvig.com
- Causal Inference for The Brave and True
- Study Notes of Udacity A/B Testing | Nancy’s Notes
- A/B Testing: Udacity Course Notes - RPubs
- A Summary of Udacity A/B Testing Course | Towards Data Science
- 1,000 Experiments Club - AB Tasty
- Bytepawn - Marton Trencseni – ab-testing
- PRODUCT SENSE “A/B TESTING” – Vivi’s Note
- Chapter 7 A/B Testing | Causal Inference
- 从数据科学家视角深入理解AB测试
数据科学博客
- Data @ Quora
- Blog | Stitch Fix Technology
- Data Science - Facebook Research
- Data Science – tech-at-instacart
- Uber Data Archives
- Data Science – Lyft Engineering
- Data - DoorDash Engineering Blog
- Netflix TechBlog
- Data Science : Spotify Engineering
- Data Science & Engineering — Shopify Engineering Blog
- Blog | LinkedIn Engineering
- rushter/data-science-blogs
- Booking.com Tech Blog
- Experimentation Platform: Articles - Microsoft Research
- Lyst Engineering Blog
- Data Science & Data Platform Engineering – Airbnb Tech Blog
- A B Testing Articles | LinkedIn Engineering
- diff.blog