[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-74195":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":10,"languages":10,"totalLinesOfCode":10,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":16,"stars7d":17,"stars30d":18,"stars90d":15,"forks30d":15,"starsTrendScore":19,"compositeScore":20,"rankGlobal":10,"rankLanguage":10,"license":21,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":24,"hasPages":22,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":38,"readmeContent":39,"aiSummary":40,"trendingCount":15,"starSnapshotCount":15,"syncStatus":14,"lastSyncTime":41,"discoverSource":42},74195,"learn-ai-engineering","ashishps1\u002Flearn-ai-engineering","ashishps1","Learn AI and LLMs from scratch using free resources","",null,5693,1399,69,2,0,18,40,220,54,40.44,"GNU General Public License v3.0",false,"main",true,[26,27,28,29,30,31,32,33,34,35,36,37],"agentic-ai","agents","ai","deep-learning","generative-ai","large-language-models","llm","machine-learning","mcp","ml","prompt-engineering","rag","2026-06-12 02:03:23","# Learn AI Engineering\n\nA comprehensive collection of free resources to learn everything about AI\u002FML, LLMs and Agents.\n\n## Mathematical Foundations\n- [Mathematics Roadmap for Machine Learning](https:\u002F\u002Fthepalindrome.org\u002Fp\u002Fthe-roadmap-of-mathematics-for-machine-learning)\n- [Essence of Linear Algebra - 3Blue1Brown](https:\u002F\u002Fwww.youtube.com\u002Fplaylist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab)\n- [Probability & Statistics - Khan Academy](https:\u002F\u002Fwww.khanacademy.org\u002Fmath\u002Fstatistics-probability)\n- [Statistics Fundamentals - Josh Strarmer](https:\u002F\u002Fwww.youtube.com\u002Fplaylist?list=PLblh5JKOoLUK0FLuzwntyYI10UQFUhsY9)\n- [Mathematics for Machine Learning Specialization - Coursera (Andrew Ng)](https:\u002F\u002Fwww.coursera.org\u002Fspecializations\u002Fmathematics-machine-learning)\n\n## Python\n- [AI Python for Beginners - Deeplearning.ai](https:\u002F\u002Fwww.deeplearning.ai\u002Fshort-courses\u002Fai-python-for-beginners\u002F)\n\n## AI & ML Fundamentals\n- [Machine Learning Crash Course - Google](https:\u002F\u002Fdevelopers.google.com\u002Fmachine-learning\u002Fcrash-course)\n- [AI for Beginners – Microsoft](https:\u002F\u002Fmicrosoft.github.io\u002FAI-For-Beginners\u002F)\n- [Elements of AI – University of Helsinki](https:\u002F\u002Fcourse.elementsofai.com\u002F)\n- [Machine Learning Playlist - Josh Strarmer](https:\u002F\u002Fwww.youtube.com\u002Fplaylist?list=PLblh5JKOoLUICTaGLRoHQDuF_7q2GfuJF)\n- [Machine Learning Specialization - Coursera](https:\u002F\u002Fwww.coursera.org\u002Fspecializations\u002Fmachine-learning-introduction)\n\n### Machine Learning Frameworks\n- [Scikit-learn](https:\u002F\u002Fscikit-learn.org\u002Fstable\u002F)\n- [XGBoost](https:\u002F\u002Fxgboost.ai\u002F)\n- [LightGBM](https:\u002F\u002Flightgbm.readthedocs.io\u002Fen\u002Fstable\u002F)\n- [CatBoost](https:\u002F\u002Fcatboost.ai\u002F)\n\n## Deep Learning\n- [Deep Learning Specialization - Coursera (Andrew Ng)](https:\u002F\u002Fwww.coursera.org\u002Fspecializations\u002Fdeep-learning)\n- [Practical Deep Learning for Coders - Fast.ai](https:\u002F\u002Fcourse.fast.ai\u002F)\n- [Mathematics for Deep Learning](https:\u002F\u002Fd2l.ai\u002Fchapter_appendix-mathematics-for-deep-learning\u002F)\n- [Deep Learning Playlist - Josh Starmer](https:\u002F\u002Fwww.youtube.com\u002Fplaylist?list=PLblh5JKOoLUIxGDQs4LFFD--41Vzf-ME1)\n\n### Deep Learning Frameworks\n- [TensorFlow](https:\u002F\u002Fwww.tensorflow.org\u002F)\n- [PyTorch](https:\u002F\u002Fpytorch.org\u002F)\n- [Keras](https:\u002F\u002Fkeras.io\u002F)\n\n## Deep Learning Specializations\n### Computer Vision\n- [Deep Learning for Computer Vision - Stanford](https:\u002F\u002Fcs231n.stanford.edu\u002F)\n### Natural Language Processing (NLP)\n- [NLP Specialization - Coursera](https:\u002F\u002Fwww.coursera.org\u002Fspecializations\u002Fnatural-language-processing)\n### Reinforcement Learning\n- [Deep RL Course - Hugging Face](https:\u002F\u002Fhuggingface.co\u002Flearn\u002Fdeep-rl-course\u002Funit0\u002Fintroduction)\n- [Deep RL Bootcamp - UC Berkeley](https:\u002F\u002Fsites.google.com\u002Fview\u002Fdeep-rl-bootcamp\u002Flectures)\n\n## Generative AI\n- [The Building Blocks of Generative AI](https:\u002F\u002Fshriftman.substack.com\u002Fp\u002Fthe-building-blocks-of-generative)\n- [Generative AI for Beginners - Microsoft](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fgenerative-ai-for-beginners)\n- [Generative AI for Everyone - Coursera](https:\u002F\u002Fwww.coursera.org\u002Flearn\u002Fgenerative-ai-for-everyone)\n\n## Large Language Models (LLMs)\n- [The Illustrated Transformer](https:\u002F\u002Fjalammar.github.io\u002Fillustrated-transformer\u002F)\n- [Large Language Models explained briefly](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=LPZh9BOjkQs)\n- [Intro to LLMs](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=zjkBMFhNj_g&pp=ygUDbGxt)\n- [Understanding Large Language Models](https:\u002F\u002Fmagazine.sebastianraschka.com\u002Fp\u002Funderstanding-large-language-models)\n- [A Visual Guide to Reasoning LLMs](https:\u002F\u002Fnewsletter.maartengrootendorst.com\u002Fp\u002Fa-visual-guide-to-reasoning-llms)\n- [Understanding Reasoning LLMs](https:\u002F\u002Fmagazine.sebastianraschka.com\u002Fp\u002Funderstanding-reasoning-llms)\n- [Understanding Multimodal LLMs](https:\u002F\u002Fmagazine.sebastianraschka.com\u002Fp\u002Funderstanding-multimodal-llms)\n- [A Visual Guide to Mixture of Experts (MoE)](https:\u002F\u002Fnewsletter.maartengrootendorst.com\u002Fp\u002Fa-visual-guide-to-mixture-of-experts)\n- [Finetuning Large Language Models](https:\u002F\u002Fmagazine.sebastianraschka.com\u002Fp\u002Ffinetuning-large-language-models)\n- [How Transformer LLMs Work](https:\u002F\u002Fwww.deeplearning.ai\u002Fshort-courses\u002Fhow-transformer-llms-work\u002F)\n- [Building GPT from scratch - Andrej Karpathy](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=kCc8FmEb1nY)\n- [LLM Course - GitHub](https:\u002F\u002Fgithub.com\u002Fmlabonne\u002Fllm-course)\n- [LLM Course - Hugging Face](https:\u002F\u002Fhuggingface.co\u002Flearn\u002Fllm-course\u002Fchapter1\u002F1)\n- [Awesome LLM Apps - GitHub](https:\u002F\u002Fgithub.com\u002FShubhamsaboo\u002Fawesome-llm-apps)\n\n### LLM Chatbots\n- [ChatGPT](https:\u002F\u002Fchatgpt.com\u002F)\n- [Gemini](https:\u002F\u002Fgemini.google.com\u002Fapp)\n- [Claude](https:\u002F\u002Fclaude.ai\u002Fnew)\n- [Perplexity](https:\u002F\u002Fwww.perplexity.ai\u002F)\n\n### Open Source LLMs\n- [Llama](https:\u002F\u002Fwww.llama.com\u002F)\n- [Deepseek](https:\u002F\u002Fchat.deepseek.com\u002F)\n\n### LLM APIs\n- [OpenAI](https:\u002F\u002Fplatform.openai.com\u002Fdocs\u002Foverview)\n- [Anthropic](https:\u002F\u002Fdocs.anthropic.com\u002Fen\u002Fdocs\u002Foverview)\n- [Gemini - Google](https:\u002F\u002Fai.google.dev\u002Fgemini-api\u002Fdocs)\n- [Groq - Inference](https:\u002F\u002Fgroq.com\u002F)\n\n### LLM Tools & Frameworks\n- [LangChain](https:\u002F\u002Fwww.langchain.com\u002F)\n- [LlamaIndex](https:\u002F\u002Fwww.llamaindex.ai\u002F)\n- [Ollama](https:\u002F\u002Follama.com\u002F)\n- [Instructor](https:\u002F\u002Fpython.useinstructor.com\u002F)\n- [Outlines](https:\u002F\u002Fgithub.com\u002Fdottxt-ai\u002Foutlines)\n\n### LLM Based IDEs\n- [Cursor](https:\u002F\u002Fwww.cursor.com\u002F)\n- [Windsurf](https:\u002F\u002Fwindsurf.com\u002Feditor)\n- [GitHub Copilot](https:\u002F\u002Fgithub.com\u002Ffeatures\u002Fcopilot)\n\n### Agentic Coding Tools\n- [Claude Code](https:\u002F\u002Fcode.claude.com\u002Fdocs\u002Fen\u002Foverview)\n- [Codex](https:\u002F\u002Fopenai.com\u002Fcodex\u002F)\n\n## Prompt Engineering\n- [Google Prompting Essentials](https:\u002F\u002Fwww.coursera.org\u002Fgoogle-learn\u002Fprompting-essentials)\n- [ChatGPT Prompt Engineering for Developers - Deeplearning.ai](https:\u002F\u002Fwww.deeplearning.ai\u002Fshort-courses\u002Fchatgpt-prompt-engineering-for-developers\u002F)\n- [Advanced Prompting Techniques - Instructor](https:\u002F\u002Fpython.useinstructor.com\u002Fprompting\u002F)\n- [Prompt Engineering Techniques - Github](https:\u002F\u002Fgithub.com\u002FNirDiamant\u002FPrompt_Engineering)\n- [Getting Structured LLM Output - Deeplearning.ai](https:\u002F\u002Fwww.deeplearning.ai\u002Fshort-courses\u002Fgetting-structured-llm-output\u002F)\n- [God Tier Prompts](https:\u002F\u002Fwww.godtierprompts.com\u002F)\n\n## Retrieval-Augmented Generation (RAG)\n- [Introduction to RAG - Coursera](https:\u002F\u002Fwww.coursera.org\u002Fprojects\u002Fintroduction-to-rag)\n- [RAG Techniques - Github](https:\u002F\u002Fgithub.com\u002FNirDiamant\u002FRAG_Techniques)\n\n## AI Agents\n- [A Visual Guide to LLM Agents](https:\u002F\u002Fnewsletter.maartengrootendorst.com\u002Fp\u002Fa-visual-guide-to-llm-agents)\n- [Agents - Chip Huyen](https:\u002F\u002Fhuyenchip.com\u002F2025\u002F01\u002F07\u002Fagents.html)\n- [AI Agents Course - Hugging Face](https:\u002F\u002Fhuggingface.co\u002Flearn\u002Fagents-course\u002F)\n- [Building AI Browser Agents - Deeplearning.ai](https:\u002F\u002Fwww.deeplearning.ai\u002Fshort-courses\u002Fbuilding-ai-browser-agents\u002F)\n- [GenAI Agents - Github](https:\u002F\u002Fgithub.com\u002FNirDiamant\u002FGenAI_Agents)\n- [AI Agents in Action, Second Edition - Book](https:\u002F\u002Fwww.manning.com\u002Fbooks\u002Fai-agents-in-action-second-edition)\n\n## Model Context Protocol (MCP)\n- [MCP - Anthropic Guide](https:\u002F\u002Fmodelcontextprotocol.io\u002Fintroduction)\n- [Building AI Apps using MCP](https:\u002F\u002Fwww.deeplearning.ai\u002Fshort-courses\u002Fmcp-build-rich-context-ai-apps-with-anthropic\u002F)\n- [MCP Course - Hugging Face](https:\u002F\u002Fhuggingface.co\u002Flearn\u002Fmcp-course\u002Funit0\u002Fintroduction)\n- [Awesome MCP Servers - Github](https:\u002F\u002Fgithub.com\u002Fpunkpeye\u002Fawesome-mcp-servers)\n\n## MLOps & Deployment\n- [ML in Production - Coursera](https:\u002F\u002Fwww.coursera.org\u002Flearn\u002Fintroduction-to-machine-learning-in-production)\n- [Full Stack Deep Learning](https:\u002F\u002Ffullstackdeeplearning.com\u002Fcourse\u002F2022\u002F)\n- [ML System Design - Stanford](https:\u002F\u002Fstanford-cs329s.github.io\u002Fsyllabus.html)\n\n### Tools\n- [Streamlit](https:\u002F\u002Fstreamlit.io\u002F)\n- [MLflow](https:\u002F\u002Fmlflow.org\u002Fdocs\u002Flatest\u002Findex.html)\n\n## Guides\n- [OpenAI Cookbook](https:\u002F\u002Fcookbook.openai.com\u002F)\n- [Anthropic courses](https:\u002F\u002Fgithub.com\u002Fanthropics\u002Fcourses\u002Ftree\u002Fmaster)\n\n## Books\n- [Hands-On Machine Learning](https:\u002F\u002Fwww.oreilly.com\u002Flibrary\u002Fview\u002Fhands-on-machine-learning\u002F9781492032632\u002F)\n- [Deep Learning - Ian Goodfellow](https:\u002F\u002Fwww.deeplearningbook.org\u002F)\n- [Deep Learning with Python](https:\u002F\u002Fwww.amazon.in\u002FDeep-Learning-Python-Francois-Chollet\u002Fdp\u002F1617294438\u002F)\n- [Why Machines Learn](https:\u002F\u002Fwww.amazon.com\u002FWhy-Machines-Learn-Elegant-Behind\u002Fdp\u002F0593185749)\n- [Designing Machine Learning Systems](https:\u002F\u002Fwww.oreilly.com\u002Flibrary\u002Fview\u002Fdesigning-machine-learning\u002F9781098107956\u002F)\n- [AI Engineering](https:\u002F\u002Fwww.oreilly.com\u002Flibrary\u002Fview\u002Fai-engineering\u002F9781098166298\u002F)\n- [Build a LLM from Scratch](https:\u002F\u002Fwww.manning.com\u002Fbooks\u002Fbuild-a-large-language-model-from-scratch)\n- [Prompt Engineering for LLMs](https:\u002F\u002Fwww.oreilly.com\u002Flibrary\u002Fview\u002Fprompt-engineering-for\u002F9781098156145\u002F)\n- [Natural Language Processing with Transformers](https:\u002F\u002Fwww.oreilly.com\u002Flibrary\u002Fview\u002Fnatural-language-processing\u002F9781098136789\u002F)\n- [Build a Multi-Agent System (from Scratch)](https:\u002F\u002Fwww.manning.com\u002Fbooks\u002Fbuild-a-multi-agent-system-from-scratch)\n- [Build a Reasoning Model (From Scratch)](https:\u002F\u002Fwww.manning.com\u002Fbooks\u002Fbuild-a-reasoning-model-from-scratch)\n- [Build an AI Agent (From Scratch)](https:\u002F\u002Fwww.manning.com\u002Fbooks\u002Fbuild-an-ai-agent-from-scratch)\n- [Build an LLM Application (from Scratch)](https:\u002F\u002Fwww.manning.com\u002Fbooks\u002Fbuild-llm-applications-from-scratch)\n- [AI Agents in Action](https:\u002F\u002Fwww.manning.com\u002Fbooks\u002Fgpt-agents-in-action)\n- [AI Agents in Action, Second Edition](https:\u002F\u002Fwww.manning.com\u002Fbooks\u002Fai-agents-in-action-second-edition)\n- [LLMs in Production](https:\u002F\u002Fwww.manning.com\u002Fbooks\u002Fllms-in-production)\n\n## YouTube Channels\n- [Andrej Karpathy](https:\u002F\u002Fwww.youtube.com\u002F@AndrejKarpathy)\n- [3Blue1Brown](https:\u002F\u002Fwww.youtube.com\u002F@3blue1brown)\n\n## Other Resources\n- [Papers with Code](https:\u002F\u002Fpaperswithcode.com\u002F)\n- [Kaggle Competitions](https:\u002F\u002Fwww.kaggle.com\u002Fcompetitions)\n\n## Must-Read AI Papers\n- [Attention Is All You Need](https:\u002F\u002Farxiv.org\u002Fpdf\u002F1706.03762)\n- [Generative Adversarial Networks (GANs)](https:\u002F\u002Farxiv.org\u002Fabs\u002F1406.2661)\n- [GPT: Improving Language Understanding by Generative Pre-Training](https:\u002F\u002Fcdn.openai.com\u002Fresearch-covers\u002Flanguage-unsupervised\u002Flanguage_understanding_paper.pdf)\n- [GPT-3: Language Models are Few-Shot Learners](https:\u002F\u002Farxiv.org\u002Fabs\u002F2005.14165)\n- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https:\u002F\u002Farxiv.org\u002Fabs\u002F1810.04805)\n- [Chain-of-Thought Prompting Elicits Reasoning in LLMs](https:\u002F\u002Farxiv.org\u002Fabs\u002F2201.11903)\n","learn-ai-engineering项目是一个全面收集了免费资源的学习平台，旨在帮助用户从零开始学习AI、机器学习、大语言模型及智能代理等相关知识。该项目涵盖了数学基础、Python编程、AI与机器学习基础知识以及深度学习等多个领域，并提供了通往各类在线课程和教程的链接，如3Blue1Brown的线性代数精华系列、Google的机器学习速成课程等。此外，它还介绍了几种流行的机器学习框架（如Scikit-learn, TensorFlow, PyTorch）及其应用。非常适合希望系统性地掌握人工智能领域相关技能的学生、开发者或任何对该领域感兴趣的人士使用。","2026-06-11 03:49:27","high_star"]