[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-9834":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":24,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":39,"readmeContent":40,"aiSummary":41,"trendingCount":15,"starSnapshotCount":15,"syncStatus":14,"lastSyncTime":42,"discoverSource":43},9834,"AI-ML-Roadmap-from-scratch","aadi1011\u002FAI-ML-Roadmap-from-scratch","aadi1011","Become skilled in Artificial Intelligence, Machine Learning, Generative AI, Deep Learning, Data Science, Natural Language Processing, Reinforcement Learning and more with this complete 0 to 100 repository.","https:\u002F\u002Faadi1011.github.io\u002FAI-ML-Roadmap-from-scratch\u002F",null,3716,703,43,2,0,7,29,154,30,30.54,"MIT License",false,"main",true,[26,27,28,29,30,31,32,33,34,35,36,37,38],"ai","aiml","artificial-intelligence","data-science","deep-learning","hacktoberfest","hacktoberfest2025","learning","machine-learning","machine-learning-from-scratch","resources","roadmap","tutorial","2026-06-12 02:02:13","\u003Ch1 align=center> Free AI and Machine Learning Roadmap with Resources \u003C\u002Fh1>\n\n🧠 Become skilled in Artificial Intelligence, Machine Learning, Generative AI, Deep Learning, Data Science, Natural Language Processing, Reinforcement Learning and more with this complete 0 to 100 repository.\n\n💡 You can follow these modules simultaneously as well as in order given below. The modules are ranked in increasing order of difficulty. Content with a `⭐` are highly recommended.\n\n📚 These are a collection of the best free resources from YouTube and online courses, as well as other popular blogs and websites.\n\n## Contents\n\n**Learning Pathway Modules**\n- [Module 0](#module-0---before-you-start) - Before You Start\n- [Module 1](#module-1---the-math-behind-it-all) - The Math Behind It All\n- [Module 2](#module-2---building-your-foundation) - Building Your Foundation\n- [Module 3](#module-3---data-science) - Data Science\n- [Module 4](#module-4---machine-learning) - Machine Learning\n- [Module 5](#module-5---computer-vision) - Computer Vision\n- [Module 6](#module-6---deep-learning-neural-network) - Deep Learning Neural Network\n- [Module 7](#module-7---generative-ai) - Generative AI\n  - [Sub-Module 7A](#sub-module-7a---retrieval-augmented-generation-rag) - Retrieval Augmented Generation (RAG)\n- [Module 8](#module-8---natural-language-processing) - Natural Language Processing\n- [Module 9](#module-9---reinforcement-learning) - Reinforcement Learning\n- [Module 10](#module-10---agentic-ai) - Agentic AI\n- [Bonus Module](#bonus-module---advanced-learning-pathway-courses) - Advanced Learning Pathway Courses\n\n\u003Cbr>**Additional Cool Stuff**\n- [PROJECTS!](#projects)\n- [Interesting Websites to Visit](#interesting-websites-to-visit)\n- [AI Newsletters](#ai-newsletters)\n- [AI Blogs](#ai-blogs)\n- [Contribute](#contribute)\n\u003Chr>\n\n## Module 0 - Before You Start \n\nBefore you begin, it is best to build your foundations and have the set-up ready. This would help you get your system working for Python on a compiler software. \nMathematics is a foundation for everything in the world for Artificial Intelligence. Have a core in applied mathematical concepts like linear algebra, matrics and more can help you theoretically understand how machines work.\n\n| S.No          | Type          | Course Name   |\n| ------------- | ------------- | ------------- |\n| 1             |`Software`      | [Python 3.14 Download](https:\u002F\u002Fwww.python.org\u002Fdownloads\u002F)  |\n| 2             |`Software`      | [Visual Studio Code Download](https:\u002F\u002Fcode.visualstudio.com\u002Fdownload)   |\n| 3             |`Py Package`    | [Install Pip Package Installer on Python](https:\u002F\u002Fwww.geeksforgeeks.org\u002Fhow-to-install-pip-on-windows\u002F) |\n| 4             |`Py Package`      | [Common Python Libraries used for AI\u002FML](https:\u002F\u002Fgithub.com\u002Faadi1011\u002FAI-ML-Roadmap-from-scratch\u002Fblob\u002Fmain\u002FPackages.md)  |\n\n\n## Module 1 - The Math Behind It All\n\nThe domain of AI\u002FML is a vast deep ocean and it's time for you to build a boat and rafters for a smooth sail. These foundational courses in Computer Science and Python Programming will get you going strong!\n\n| S.No          | Type          | Course Name   |\n| ------------- | ------------- | ------------- |\n| 1             |`Playlist`     | [Math for Machine Learning Playlist](https:\u002F\u002Fyoutube.com\u002Fplaylist?list=PLD80i8An1OEGZ2tYimemzwC3xqkU0jKUg&si=6sZ51wadUZnscjRG)  |\n| 2             |`⭐Course`     | [NPTEL Swayam Discrete Mathematics Course](https:\u002F\u002Fonlinecourses.nptel.ac.in\u002Fnoc22_cs33\u002Fpreview)         | \n| 3             |`Course`       | [Discrete Structures via Saylor Academy](https:\u002F\u002Fwww.classcentral.com\u002Fcourse\u002Fsaylor-academy-67-cs202-discrete-structures-99529) |\n| 4             |`Lectures`     | [Linear Algebra Lecture Series from MIT](https:\u002F\u002Focw.mit.edu\u002Fcourses\u002F18-06-linear-algebra-spring-2010\u002Fdownload\u002F) |\n| 5             |`Course`       | [Fundamental Math for Data Science](https:\u002F\u002Fwww.codecademy.com\u002Flearn\u002Fpaths\u002Ffundamental-math-for-data-science)| \n\n\n\n## Module 2 - Building Your Foundation\n\nThe domain of AI\u002FML is a vast deep ocean and it's time for you to build a boat and rafters for a smooth sail. These foundational courses in Computer Science and Python Programming will get you going strong!\n\n| S.No          | Type          | Course Name   |\n| ------------- | ------------- | ------------- |\n| 1             |`Course`      | [MITx: Introduction to Computer Science and Programming Using Python](https:\u002F\u002Fwww.edx.org\u002Flearn\u002Fcomputer-science\u002Fmassachusetts-institute-of-technology-introduction-to-computer-science-and-programming-using-python)         | \n| 2             |`Course`      | [HarvardX: CS50's Introduction to Programming with Python](https:\u002F\u002Fwww.edx.org\u002Flearn\u002Fpython\u002Fharvard-university-cs50-s-introduction-to-programming-with-python)         | \n| 3             |`Website`      | [Introduction to Python - W3 Schools](https:\u002F\u002Fwww.w3schools.com\u002Fpython\u002Fpython_intro.asp)      | \n| 4             | `YouTube`      | [Learn Python in 4 Hours](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=rfscVS0vtbw)      | \n| 5             | `⭐Practice!`  | [Practice Python on HackerRank](https:\u002F\u002Fwww.hackerrank.com\u002Fdomains\u002Fpython) |\n| 6             | `Certificate`  | [Python Basic Certification](https:\u002F\u002Fwww.hackerrank.com\u002Fskills-verification\u002Fpython_basic) |\n\n\n\n\n## Module 3 - Data Science\n\nData is the new oil! Before jumping into making advanced AI, let's learn about the data that drives it. We'll cover basics of statistics and Data Science using Python in this module.\n\n| S.No          | Type          | Course Name   | \n| ------------- | ------------- | ------------- | \n| _Bonus_       | `YouTube`     | [Quick 5 Minute Intro to Data Science](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=X3paOmcrTjQ)         |\n| 1             | `YouTube`      | [Data Science Overview](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=ua-CiDNNj30)           | \n| 2             | `Website`      | [Data Science Introduction](https:\u002F\u002Fwww.w3schools.com\u002Fdatascience\u002Fds_introduction.asp)           | \n| 3             | `YouTube`     | [Python for Data Science](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=LHBE6Q9XlzI)         |  \n| 4             | `Course`      | [Google Data Analytics Professional Certificate](https:\u002F\u002Fwww.coursera.org\u002Fprofessional-certificates\u002Fgoogle-data-analytics) |  \n| 5             | `⭐Course`     | [IBM Data Science Professional Certificate](https:\u002F\u002Fwww.coursera.org\u002Fprofessional-certificates\u002Fibm-data-science)         | \n\n\n\n\n\n## Module 4 - Machine Learning\n\nTime to use that data to train a machine on how to learn them. Machine learning is the science of computer algorithms that help machines learn and improve from data analysis without explicit programming. _THAT'S SO COOL!_ \n\n| S.No          | Type          | Course Name   | \n| ------------- | ------------- | ------------- | \n| 1             | `Website`     | [Introductory Article on Machine Learning - Spiceworks](https:\u002F\u002Fwww.spiceworks.com\u002Ftech\u002Fartificial-intelligence\u002Farticles\u002Fwhat-is-ml\u002F) | \n| 2             | `⭐Course`      | [HarvardX: Data Science: Machine Learning](https:\u002F\u002Fwww.edx.org\u002Flearn\u002Fmachine-learning\u002Fharvard-university-data-science-machine-learning)         | \n| 3             | `Website`     | [Machine Learning Tutorial - GFG](https:\u002F\u002Fwww.geeksforgeeks.org\u002Fmachine-learning\u002F) | \n| 4             | `Course`      | [Explore Azure with OpenAI](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Ftraining\u002Fmodules\u002Fexplore-azure-openai\u002F)|\n| _5*_             | `Course`      | [Machine Learning Specialization by Andrew Ng](https:\u002F\u002Fwww.coursera.org\u002Fspecializations\u002Fmachine-learning-introduction) |\n| 6              | `Course`      | [Machine Learning Engineer Learning Path from Google Cloud Skills Boost](https:\u002F\u002Fwww.cloudskillsboost.google\u002Fpaths\u002F17) \n\n_*❗ The ML Specialization by Andrew NG is a highly specialized and industry level course by one of the most promient AI scientist - Andrew NG. It is an expert level course and is highly recommened to do one you get a good grasp of the foundational knowledge._\n\n\n\n\n## Module 5 - Computer Vision\n\nGiving the power of vision to our intelligent computers! Computer Vision trains computers to interpret and understand the visual world, just the way we see it (_or in an more advanced way ;)_)\n\n| S.No          | Type          | Course Name   |\n| ------------- | ------------- | ------------- |\n| 1             | `YouTube`      | [Computer Vision Crash Course Overview](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=-4E2-0sxVUM&pp=ygUPY29tcHV0ZXIgdmlzaW9u)         |\n| 2             | `YouTube`      | [OpenCV Course - Full Tutorial with Python](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=oXlwWbU8l2o)         |\n| 3             | `Course`      | [OpenCV Bootcamp](https:\u002F\u002Fopencv.org\u002Funiversity\u002Ffree-opencv-course\u002F)         |\n| 4             | `⭐Course`      | [Computer Vision Essentials](https:\u002F\u002Fwww.mygreatlearning.com\u002Facademy\u002Flearn-for-free\u002Fcourses\u002Fcomputer-vision-essentials)         |\n| 5             | `Playlist`      |  (VERY ADVANCED) [Stanford Computer Vision Lectures](https:\u002F\u002Fyoutube.com\u002Fplaylist?list=PLf7L7Kg8_FNxHATtLwDceyh72QQL9pvpQ&si=51MnhQ_APncU-RVk)         |\n\n\n\n## Module 6 - Deep Learning Neural Network \n\nTime to harness the power of our human brain to develop something that resembles the powers of a human brain. Neural Networks help you understand how information is processed from raw data like the human brain to mimic desired outputs.\n\n| S.No          | Type          | Course Name   |\n| ------------- | ------------- | ------------- |\n| 1             | `Course`      | [DeepLearning.AI Neural Networks and Deep Learning](https:\u002F\u002Fwww.coursera.org\u002Flearn\u002Fneural-networks-deep-learning)         |\n| 2             | `Course`      | [Neural Networks and Deep Learning](https:\u002F\u002Fwww.classcentral.com\u002Fcourse\u002Fneural-networks-deep-learning-9058)               |\n| 3             | `Course`      | [Convolutional Neural Networks](https:\u002F\u002Fwww.coursera.org\u002Flearn\u002Fconvolutional-neural-networks)               |\n| 4             | `⭐YouTube`     | [Deep Learning Crash Course for Beginners](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=VyWAvY2CF9c)    |\n| 5             | `Playlist`     | [Neural Networks: Zero to Hero](https:\u002F\u002Fyoutube.com\u002Fplaylist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ&si=xfuffzwv3I9MT0Lc)    |\n\n\n\n\n## Module 7 - Generative AI\n\nThe big buzz word everywhere! Create text, images, audios, videos, and more all thanks to Generative Adversarial Networks!\n\n| S.No          | Type          | Course Name   |\n| ------------- | ------------- | ------------- |\n| 1             | `Course`      | [Microsoft Fundamentals of Generative AI](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Ftraining\u002Fmodules\u002Ffundamentals-generative-ai\u002F)         |\n| 2             | `Course`      | [Microsoft Responsible Generative AI](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Ftraining\u002Fmodules\u002Fresponsible-generative-ai\u002F)         |\n| 3             | `⭐YouTube`     | [Generative AI in a Nutshell](https:\u002F\u002Fyoutu.be\u002F2IK3DFHRFfw?si=V9I81wsPVAhkuinS) |\n| 4             | `Course`      | [Generative Adversarial Networks (GANs) Specialization](https:\u002F\u002Fwww.coursera.org\u002Fspecializations\u002Fgenerative-adversarial-networks-gans) |\n| 5             | `E-Book`      | [Generative AI and LLMs for Dummies](.\u002Fresources\u002FGenerative-AI-and-LLMs-for-Dummies.pdf) |\n| 6             | `Course`      | [Generative AI Learning Path by Google Cloud Skills Boost](https:\u002F\u002Fwww.cloudskillsboost.google\u002Fpaths\u002F118) |\n| 7             | `YouTube`     | [Generative AI for Developers](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=F0GQ0l2NfHA) |\n\n### Sub-Module 7A - Retrieval Augmented Generation (RAG)\nRetrieval-augmented generation (RAG) is a natural language processing (NLP) technique that combines the capabilities of traditional information retrieval systems with the strengths of generative large language models (LLMs)\n\n| S.No          | Type          | Course Name   |\n| ------------- | ------------- | ------------- |\n| 1             | `Course`      | [Retrieval Augmented Generation Introduction (RXM403)](https:\u002F\u002Ftraining.linuxfoundation.org\u002Ftraining\u002Fretrieval-augmented-generation-rag-intro-rxm403\u002F)         |\n| 2             | `Project ` | [Guided Project on RAG](https:\u002F\u002Fwww.coursera.org\u002Fprojects\u002Fintroduction-to-rag) |\n| 3             | `YouTube`   | [Learn RAG From Scratch](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=sVcwVQRHIc8&pp=ygUeUmV0cmlldmFsIGFndW1lbnRlZCBnZW5lcmF0aW9u) |\n| 4             | `YouTube`   | [Learn RAG, LangChain, Vector DB's, with this project, FULL COURSE](https:\u002F\u002Fyoutu.be\u002FShEOoJLSLbI) |\n\n\n## Module 8 - Natural Language Processing\n\nEnglish, Spanish, French, Hindi, Tamil, Russian, Python, Java, C++ and wait what? Let's learn how can we help computers understand our human language better (the natural language)\n\n| S.No          | Type          | Course Name   |\n| ------------- | ------------- | ------------- |\n| 1             | `Website`     | [How To Get Started with NLP](https:\u002F\u002Ftowardsdatascience.com\u002Fhow-to-get-started-in-nlp-6a62aa4eaeff) |\n| 2             | `⭐Playlist`      | [Tensorflow's NLP Zero to Hero](https:\u002F\u002Fyoutube.com\u002Fplaylist?list=PLQY2H8rRoyvzDbLUZkbudP-MFQZwNmU4S&si=CTpntcabz40_MDLR)         |\n| 3             | `YouTube`     | [Natural Language Processing Pipeline](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=6I-Alfkr5K4) |\n\n\n\n## Module 9 - Reinforcement Learning\n\nWalk, fall, get up, learn, repeat. Just like how humans learn through experiences on what to do and what not to do, AI is no different! \n\n| S.No          | Type          | Course Name   |\n| ------------- | ------------- | ------------- |\n| 1             | `Playlist`    | [Reinforcement Learning By The Book](https:\u002F\u002Fwww.youtube.com\u002Fplaylist?list=PLzvYlJMoZ02Dxtwe-MmH4nOB5jYlMGBjr)         |\n| 2             | `YouTube`     | [RL Basics from Scratch](https:\u002F\u002Fyoutu.be\u002FvXtfdGphr3c?si=fnC5onHgc2Kmaeww) |\n| 3              | `Website`     | [Reinforcement Learning Tutorial - JavaTPoint](https:\u002F\u002Fwww.javatpoint.com\u002Freinforcement-learning) |\n| 4             | `⭐Website`      | [Deep Reinforcement Learning Course - HuggingFace](https:\u002F\u002Fhuggingface.co\u002Flearn\u002Fdeep-rl-course\u002Fen\u002Funit0\u002Fintroduction) |\n\n\n\n## Module 10 - Agentic AI\n\nDon't just provide the solutions, start acting on it. Agentic AI workflows integrate AI and operations to fuel the next wave automation like never before. \n\n| S.No          | Type          | Course Name   |\n| ------------- | ------------- | ------------- |\n| 1             | `⭐YouTube`     | [AI Agents Fundamentals in 7 Minutes](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=dJrgZrPKJfQ)               |\n| 2             | `YouTube`    | [Getting Started with LangFlow](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=knPg4KdKU6w&pp=ygUOTGVhcm4gbGFuZ2Zsb3c%3D)         |\n| 3             | `YouTube`     | [Building RAG Based LLM App using LangFlow ](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=rz40ukZ3krQ&pp=ygUOTGVhcm4gbGFuZ2Zsb3c%3D) |\n| 4              | `YouTube`     | [Building a Team of AI Agents in n8n with No Code](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=9FuNtfsnRNo) |\n| 5             | `Website`      | [n8n Documentation](https:\u002F\u002Fdocs.n8n.io\u002F) |\n| 6             | `Website`      | [Generative AI vs Agentic AI - Forbes](https:\u002F\u002Fwww.forbes.com\u002Fsites\u002Fbernardmarr\u002F2025\u002F02\u002F03\u002Fgenerative-ai-vs-agentic-ai-the-key-differences-everyone-needs-to-know\u002F)       |\n\n\n\n## `Bonus` Module - Advanced Learning Pathway Courses\n\nAdditional bonus courses and problem solving exercises.\n\n| S.No          | Course Name   |\n| ------------- | ------------- |\n| 1             | [Stanford Machine Learning Specialization](https:\u002F\u002Fwww.coursera.org\u002Fspecializations\u002Fmachine-learning-introduction) |\n| 2             | [Google: Google AI for Anyone](https:\u002F\u002Fwww.edx.org\u002Flearn\u002Fartificial-intelligence\u002Fgoogle-google-ai-for-anyone)         |\n| 3             | [IBM AI Foundations for Business Specialization](https:\u002F\u002Fwww.coursera.org\u002Fspecializations\u002Fibm-ai-foundations-for-business)         |\n| 4             | [Solve Artificial Intelligence Problems on HackerRank](https:\u002F\u002Fwww.hackerrank.com\u002Fdomains\u002Fai) |\n| 5             | [Solve Functional Programming on HackerRank](https:\u002F\u002Fwww.hackerrank.com\u002Fdomains\u002Falgorithms) |\n\n\n## PROJECTS! \n* 20 Popular Deep Learning Projects - [TheCleverProgrammer Blog](https:\u002F\u002Fthecleverprogrammer.com\u002F2020\u002F11\u002F22\u002Fdeep-learning-projects-with-python\u002F)\n* 500 AI, Machine learning, Deep learning, Computer vision, NLP Projects with code - [GitHub Repo](https:\u002F\u002Fgithub.com\u002Fashishpatel26\u002F500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code)\n* Machine Learning Projects - [GeeksForGeeks](https:\u002F\u002Fwww.geeksforgeeks.org\u002Fmachine-learning-projects\u002F)\n* 15 Python Reinforcement Learning Project Ideas for Beginners - [Project Pro](https:\u002F\u002Fwww.projectpro.io\u002Farticle\u002Freinforcement-learning-projects-ideas-for-beginners-with-code\u002F521)\n\n## Interesting Websites to Visit:\n* [AI Club - SIT Pune](https:\u002F\u002Fwww.instagram.com\u002Faiclub.sit\u002F)\n* [AI WareHouse](https:\u002F\u002Fwww.youtube.com\u002F@aiwarehouse)\n* [Google Talk to Books](https:\u002F\u002Fbooks.google.com\u002Ftalktobooks\u002F)\n* [Google Semantris Machine Learning Word Game](https:\u002F\u002Fresearch.google.com\u002Fsemantris\u002F)\n* [Replika AI Avatars](https:\u002F\u002Freplika.com\u002F)\n* [AI Music, Text to Speech, and Voice to Voice](https:\u002F\u002Ffakeyou.com\u002F)\n  \n### AI Newsletters\n* [The Rundown AI](https:\u002F\u002Fwww.therundown.ai\u002F)\n* [Mindstream](https:\u002F\u002Fwww.mindstream.news\u002F)\n* [AI Breakfast](https:\u002F\u002Faibreakfast.beehiiv.com\u002F)\n* [TLDR AI](https:\u002F\u002Ftldr.tech\u002Fai)\n* [The Neuron](https:\u002F\u002Fwww.theneurondaily.com\u002F)\n\n### AI Blogs\n* [Google AI Blogs](https:\u002F\u002Fai.google\u002Fdiscover\u002Fblogs\u002F)\n* [Distill Publications](https:\u002F\u002Fdistill.pub\u002F)\n* [Machine Learning Mastery](https:\u002F\u002Fmachinelearningmastery.com\u002Fblog\u002F)\n\n\n\n## Contribute\n\nMany hands make light work! I would be more than happy if you are willing to contribute to this repository and help others learn better.\n\nMake sure to read the [`CONTRIBUTING`](https:\u002F\u002Fgithub.com\u002Faadi1011\u002FAI-ML-Roadmap-from-scratch\u002Fblob\u002Fmain\u002FCONTRIBUTING.md) file to understand more on how you can help!\n","该项目提供了一个从零开始全面掌握人工智能、机器学习、生成式AI、深度学习、数据科学、自然语言处理和强化学习等领域的免费资源路线图。它包含了一系列模块，每个模块都按照难度递增的顺序排列，涵盖了从数学基础到高级应用的全过程。项目精心挑选了来自YouTube、在线课程以及其他知名博客和网站的最佳免费资源，并提供了推荐的学习路径。适合任何希望系统性地学习AI相关知识和技术的初学者或有一定基础的学习者使用。","2026-06-11 03:24:57","top_topic"]