[![GitHub license](https://img.shields.io/github/license/microsoft/ML-For-Beginners.svg)](https://github.com/microsoft/ML-For-Beginners/blob/master/LICENSE) [![GitHub contributors](https://img.shields.io/github/contributors/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/graphs/contributors/) [![GitHub issues](https://img.shields.io/github/issues/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/issues/) [![GitHub pull-requests](https://img.shields.io/github/issues-pr/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/pulls/) [![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com) [![GitHub watchers](https://img.shields.io/github/watchers/microsoft/ML-For-Beginners.svg?style=social&label=Watch)](https://GitHub.com/microsoft/ML-For-Beginners/watchers/) [![GitHub forks](https://img.shields.io/github/forks/microsoft/ML-For-Beginners.svg?style=social&label=Fork)](https://GitHub.com/microsoft/ML-For-Beginners/network/) [![GitHub stars](https://img.shields.io/github/stars/microsoft/ML-For-Beginners.svg?style=social&label=Star)](https://GitHub.com/microsoft/ML-For-Beginners/stargazers/) ### 🌐 Multi-Language Support #### Supported via GitHub Action (Automated & Always Up-to-Date) [Arabic](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgarian](../bg/README.md) | [Burmese (Myanmar)](../my/README.md) | [Chinese (Simplified)](../zh-CN/README.md) | [Chinese (Traditional, Hong Kong)](../zh-HK/README.md) | [Chinese (Traditional, Macau)](../zh-MO/README.md) | [Chinese (Traditional, Taiwan)](../zh-TW/README.md) | [Croatian](../hr/README.md) | [Czech](../cs/README.md) | [Danish](../da/README.md) | [Dutch](../nl/README.md) | [Estonian](../et/README.md) | [Finnish](../fi/README.md) | [French](../fr/README.md) | [German](../de/README.md) | [Greek](../el/README.md) | [Hebrew](../he/README.md) | [Hindi](../hi/README.md) | [Hungarian](../hu/README.md) | [Indonesian](../id/README.md) | [Italian](../it/README.md) | [Japanese](../ja/README.md) | [Kannada](../kn/README.md) | [Korean](../ko/README.md) | [Lithuanian](../lt/README.md) | [Malay](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](./README.md) | [Norwegian](../no/README.md) | [Persian (Farsi)](../fa/README.md) | [Polish](../pl/README.md) | [Portuguese (Brazil)](../pt-BR/README.md) | [Portuguese (Portugal)](../pt-PT/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romanian](../ro/README.md) | [Russian](../ru/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenian](../sl/README.md) | [Spanish](../es/README.md) | [Swahili](../sw/README.md) | [Swedish](../sv/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkish](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamese](../vi/README.md) > **Prefer to Clone Locally?** > Dis repo get 50+ language translations wey dey make di download size big pass. To clone without di translation dem, use sparse checkout: > ```bash > git clone --filter=blob:none --sparse https://github.com/microsoft/ML-For-Beginners.git > cd ML-For-Beginners > git sparse-checkout set --no-cone '/*' '!translations' '!translated_images' > ``` > Dis go give you everything wey you need to complete di course fast. #### Join Our Community [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) We get one Discord learn wit AI series wey never stop, learn more and join us for [Learn with AI Series](https://aka.ms/learnwithai/discord) from 18 - 30 September, 2025. You go fit get tips and tricks on how to use GitHub Copilot for Data Science. ![Learn with AI series](../../translated_images/pcm/3.9b58fd8d6c373c20.webp) # Machine Learning for Beginners - A Curriculum > 🌍 Travel around di world as we dey explore Machine Learning through world cultures 🌍 Cloud Advocates for Microsoft happy to offer 12-week, 26-lesson curriculum wey dey all about **Machine Learning**. Inside dis curriculum, you go learn wetin dem dey call **classic machine learning**, mainly using Scikit-learn as library and no go enter deep learning wey dey inside our [AI for Beginners' curriculum](https://aka.ms/ai4beginners). You fit also pair dis lessons with our ['Data Science for Beginners' curriculum](https://aka.ms/ds4beginners). Travel with us around di world as we apply di classic techniques to data from many parts of di world. Every lesson get pre- and post-lesson quizzes, written instructions to complete di lesson, solution, assignment, and more. Our project-based methodology allow you to learn as you dey build, na better way for new skills to stick. **✍️ Big thanks to our authors** Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu and Amy Boyd **🎨 Thanks also go to our illustrators** Tomomi Imura, Dasani Madipalli, and Jen Looper **🙏 Special thanks 🙏 to our Microsoft Student Ambassador authors, reviewers, and content contributors**, especially Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila, and Snigdha Agarwal **🤩 Extra gratitude to Microsoft Student Ambassadors Eric Wanjau, Jasleen Sondhi, and Vidushi Gupta for our R lessons!** # Getting Started Follow dis steps: 1. **Fork the Repository**: Click di "Fork" button for di top-right corner of dis page. 2. **Clone the Repository**: `git clone https://github.com/microsoft/ML-For-Beginners.git` > [Find all di extra resources for dis course inside our Microsoft Learn collection](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) > 🔧 **Need help?** Check our [Troubleshooting Guide](TROUBLESHOOTING.md) for solutions to common problems with installation, setup, and running lessons. **[Students](https://aka.ms/student-page)**, to use dis curriculum, fork di full repo to your own GitHub account and complete di exercises by yourself or wit group: - Start wit pre-lecture quiz. - Read di lecture and complete di activities, pause and think for every knowledge check. - Try make you create di projects by understanding di lessons well instead of just running di solution code; but if you want, dat code dey available inside di `/solution` folders for each project-oriented lesson. - Take di post-lecture quiz. - Complete di challenge. - Complete di assignment. - After you don finish one lesson group, go visit di [Discussion Board](https://github.com/microsoft/ML-For-Beginners/discussions), and "learn out loud" by filling di correct PAT rubric. PAT na Progress Assessment Tool, na rubric wey you fill to help your learning grow. You fit also respond to other PATs so we all fit learn together. > For more study, we recommend you follow these [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-77952-leestott) modules and learning paths. **Teachers**, we don [include some suggestions](for-teachers.md) on how to use dis curriculum. --- ## Video walkthroughs Some lessons get short video form. You fit find all dese inside di lessons or for di [ML for Beginners playlist on the Microsoft Developer YouTube channel](https://aka.ms/ml-beginners-videos) by clicking di image below. [![ML for beginners banner](../../translated_images/pcm/ml-for-beginners-video-banner.63f694a100034bc6.webp)](https://aka.ms/ml-beginners-videos) --- ## Meet the Team [![Promo video](../../images/ml.gif)](https://youtu.be/Tj1XWrDSYJU) **Gif by** [Mohit Jaisal](https://linkedin.com/in/mohitjaisal) > 🎥 Click di picture wey dey above for video about di project and di people wey create am! --- ## Pedagogy We choose two teaching principles as we build dis curriculum: to make am hands-on **project-based** and get **frequent quizzes** inside. Plus, dis curriculum get one common **theme** to make am balanced. By making sure say content match projects, e go make learning more interesting for students and e go help concepts stay for head well. Plus, low-stakes quiz before class dey help student focus to learn di topic, and another quiz after class go help keep di memory strong. Dis curriculum dey flexible and fun, and you fit take am whole or part. Projects start small and get more complex as di 12-week cycle dey end. Dis curriculum even get one postscript about real-world ways di ML fit take, for extra credit or discussion base. > Find our [Code of Conduct](CODE_OF_CONDUCT.md), [Contributing](CONTRIBUTING.md), [Translation](TRANSLATIONS.md), and [Troubleshooting](TROUBLESHOOTING.md) guidelines. We dey always welcome your constructive feedback! ## Each lesson get - optional sketchnote - optional supplemental video - video walkthrough (some lessons only) - [pre-lecture warmup quiz](https://ff-quizzes.netlify.app/en/ml/) - written lesson - for project-based lessons, step-by-step guides on how to build the project - knowledge checks - challenge - supplemental reading - assignment - [post-lecture quiz](https://ff-quizzes.netlify.app/en/ml/) > **Note about languages**: Most lessons dey for Python, but plenty still dey for R too. To finish one R lesson, waka go `/solution` folder and find R lessons. Dem get .rmd extension wey mean **R Markdown** file, wey be embedding of `code chunks` (fit be R or other languages) and `YAML header` (wey show how to format outputs like PDF) for one `Markdown document`. So, e be one correct way make you combine your code, wetin e produce, and your thoughts, by writing all down for Markdown. Plus, R Markdown documents fit convert to output formats like PDF, HTML, or Word. > **One tok bout quizzes**: All quizzes dey inside [Quiz App folder](../../quiz-app), get 52 quizzes for three questions each. Dem link from inside di lessons but you fit run di quiz app for your own machine; follow di instruction wey dey inside di `quiz-app` folder make you fit host am local or deploy am for Azure. | Lesson Number | Topic | Lesson Grouping | Learning Objectives | Linked Lesson | Author | | :-----------: | :------------------------------------------------------------: | :-------------------------------------------------: | ------------------------------------------------------------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------: | | 01 | Introduction to machine learning | [Introduction](1-Introduction/README.md) | Learn di basic tins wey dey back machine learning | [Lesson](1-Introduction/1-intro-to-ML/README.md) | Muhammad | | 02 | The History of machine learning | [Introduction](1-Introduction/README.md) | Learn di history wey dey back dis kain field | [Lesson](1-Introduction/2-history-of-ML/README.md) | Jen and Amy | | 03 | Fairness and machine learning | [Introduction](1-Introduction/README.md) | Wetin be di important philosophical tins about fairness wey students suppose consider wen dem dey build and use ML models? | [Lesson](1-Introduction/3-fairness/README.md) | Tomomi | | 04 | Techniques for machine learning | [Introduction](1-Introduction/README.md) | Wetin kain techniques ML researchers dey use make dem build ML models? | [Lesson](1-Introduction/4-techniques-of-ML/README.md) | Chris and Jen | | 05 | Introduction to regression | [Regression](2-Regression/README.md) | Start to use Python and Scikit-learn for regression models | [Python](2-Regression/1-Tools/README.md) • [R](../../2-Regression/1-Tools/solution/R/lesson_1.html) | Jen • Eric Wanjau | | 06 | North American pumpkin prices 🎃 | [Regression](2-Regression/README.md) | Make diagram and clean data before ML | [Python](2-Regression/2-Data/README.md) • [R](../../2-Regression/2-Data/solution/R/lesson_2.html) | Jen • Eric Wanjau | | 07 | North American pumpkin prices 🎃 | [Regression](2-Regression/README.md) | Build linear and polynomial regression models | [Python](2-Regression/3-Linear/README.md) • [R](../../2-Regression/3-Linear/solution/R/lesson_3.html) | Jen and Dmitry • Eric Wanjau | | 08 | North American pumpkin prices 🎃 | [Regression](2-Regression/README.md) | Build logistic regression model | [Python](2-Regression/4-Logistic/README.md) • [R](../../2-Regression/4-Logistic/solution/R/lesson_4.html) | Jen • Eric Wanjau | | 09 | A Web App 🔌 | [Web App](3-Web-App/README.md) | Build web app wey go use your trained model | [Python](3-Web-App/1-Web-App/README.md) | Jen | | 10 | Introduction to classification | [Classification](4-Classification/README.md) | Clean, prepare, and make diagram of your data; introduction to classification | [Python](4-Classification/1-Introduction/README.md) • [R](../../4-Classification/1-Introduction/solution/R/lesson_10.html) | Jen and Cassie • Eric Wanjau | | 11 | Delicious Asian and Indian cuisines 🍜 | [Classification](4-Classification/README.md) | Introduction to classifiers | [Python](4-Classification/2-Classifiers-1/README.md) • [R](../../4-Classification/2-Classifiers-1/solution/R/lesson_11.html) | Jen and Cassie • Eric Wanjau | | 12 | Delicious Asian and Indian cuisines 🍜 | [Classification](4-Classification/README.md) | More classifiers | [Python](4-Classification/3-Classifiers-2/README.md) • [R](../../4-Classification/3-Classifiers-2/solution/R/lesson_12.html) | Jen and Cassie • Eric Wanjau | | 13 | Delicious Asian and Indian cuisines 🍜 | [Classification](4-Classification/README.md) | Build recommender web app wit your model | [Python](4-Classification/4-Applied/README.md) | Jen | | 14 | Introduction to clustering | [Clustering](5-Clustering/README.md) | Clean, prepare, and draw diagram for your data; Introduction to clustering | [Python](5-Clustering/1-Visualize/README.md) • [R](../../5-Clustering/1-Visualize/solution/R/lesson_14.html) | Jen • Eric Wanjau | | 15 | Exploring Nigerian Musical Tastes 🎧 | [Clustering](5-Clustering/README.md) | Explore di K-Means clustering method | [Python](5-Clustering/2-K-Means/README.md) • [R](../../5-Clustering/2-K-Means/solution/R/lesson_15.html) | Jen • Eric Wanjau | | 16 | Introduction to natural language processing ☕️ | [Natural language processing](6-NLP/README.md) | Learn basics about NLP by building simple bot | [Python](6-NLP/1-Introduction-to-NLP/README.md) | Stephen | | 17 | Common NLP Tasks ☕️ | [Natural language processing](6-NLP/README.md) | Deep your NLP knowledge by understanding common tasks wey dem need sometimes for language structures | [Python](6-NLP/2-Tasks/README.md) | Stephen | | 18 | Translation and sentiment analysis ♥️ | [Natural language processing](6-NLP/README.md) | Translation and sentiment analysis with Jane Austen | [Python](6-NLP/3-Translation-Sentiment/README.md) | Stephen | | 19 | Romantic hotels of Europe ♥️ | [Natural language processing](6-NLP/README.md) | Sentiment analysis with hotel reviews 1 | [Python](6-NLP/4-Hotel-Reviews-1/README.md) | Stephen | | 20 | Romantic hotels of Europe ♥️ | [Natural language processing](6-NLP/README.md) | Sentiment analysis with hotel reviews 2 | [Python](6-NLP/5-Hotel-Reviews-2/README.md) | Stephen | | 21 | Introduction to time series forecasting | [Time series](7-TimeSeries/README.md) | Introduction to time series forecasting | [Python](7-TimeSeries/1-Introduction/README.md) | Francesca | | 22 | ⚡️ World Power Usage ⚡️ - time series forecasting with ARIMA | [Time series](7-TimeSeries/README.md) | Time series forecasting with ARIMA | [Python](7-TimeSeries/2-ARIMA/README.md) | Francesca | | 23 | ⚡️ World Power Usage ⚡️ - time series forecasting with SVR | [Time series](7-TimeSeries/README.md) | Time series forecasting wit Support Vector Regressor | [Python](7-TimeSeries/3-SVR/README.md) | Anirban | | 24 | Introduction to reinforcement learning | [Reinforcement learning](8-Reinforcement/README.md) | Introduction to reinforcement learning with Q-Learning | [Python](8-Reinforcement/1-QLearning/README.md) | Dmitry | | 25 | Help Peter avoid the wolf! 🐺 | [Reinforcement learning](8-Reinforcement/README.md) | Reinforcement learning Gym | [Python](8-Reinforcement/2-Gym/README.md) | Dmitry | | Postscript | Real-World ML scenarios and applications | [ML in the Wild](9-Real-World/README.md) | Interesting and true true real-world applications of classical ML | [Lesson](9-Real-World/1-Applications/README.md) | Team | | Postscript | Model Debugging in ML using RAI dashboard | [ML in the Wild](9-Real-World/README.md) | Model Debugging in Machine Learning using Responsible AI dashboard components | [Lesson](9-Real-World/2-Debugging-ML-Models/README.md) | Ruth Yakubu | > [find all additional resources for this course in our Microsoft Learn collection](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) ## Offline access You fit run dis documentation offline by using [Docsify](https://docsify.js.org/#/). Fork dis repo, [install Docsify](https://docsify.js.org/#/quickstart) for your own machine, then for di root folder of dis repo, type `docsify serve`. Di website go dey for port 3000 for your localhost: `localhost:3000`. ## PDFs Find pdf of di curriculum with links [here](https://microsoft.github.io/ML-For-Beginners/pdf/readme.pdf). ## 🎒 Other Courses Our team dey produce other courses! Check am out: ### LangChain [![LangChain4j for Beginners](https://img.shields.io/badge/LangChain4j%20for%20Beginners-22C55E?style=for-the-badge&&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchain4j-for-beginners) [![LangChain.js for Beginners](https://img.shields.io/badge/LangChain.js%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin) [![LangChain for Beginners](https://img.shields.io/badge/LangChain%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https://github.com/microsoft/langchain-for-beginners?WT.mc_id=m365-94501-dwahlin) --- ### Azure / Edge / MCP / Agents [![AZD for Beginners](https://img.shields.io/badge/AZD%20for%20Beginners-0078D4?style=for-the-badge&labelColor=E5E7EB&color=0078D4)](https://github.com/microsoft/AZD-for-beginners?WT.mc_id=academic-105485-koreyst) [![Edge AI for Beginners](https://img.shields.io/badge/Edge%20AI%20for%20Beginners-00B8E4?style=for-the-badge&labelColor=E5E7EB&color=00B8E4)](https://github.com/microsoft/edgeai-for-beginners?WT.mc_id=academic-105485-koreyst) [![MCP for Beginners](https://img.shields.io/badge/MCP%20for%20Beginners-009688?style=for-the-badge&labelColor=E5E7EB&color=009688)](https://github.com/microsoft/mcp-for-beginners?WT.mc_id=academic-105485-koreyst) [![AI Agents for Beginners](https://img.shields.io/badge/AI%20Agents%20for%20Beginners-00C49A?style=for-the-badge&labelColor=E5E7EB&color=00C49A)](https://github.com/microsoft/ai-agents-for-beginners?WT.mc_id=academic-105485-koreyst) --- ### Generative AI Series [![Generative AI for Beginners](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) [![Generative AI (.NET)](https://img.shields.io/badge/Generative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst) [![Generative AI (Java)](https://img.shields.io/badge/Generative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst) [![Generative AI (JavaScript)](https://img.shields.io/badge/Generative%20AI%20(JavaScript)-E879F9?style=for-the-badge&labelColor=E5E7EB&color=E879F9)](https://github.com/microsoft/generative-ai-with-javascript?WT.mc_id=academic-105485-koreyst) --- ### Core Learning [![ML for Beginners](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) [![Data Science for Beginners](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) [![AI for Beginners](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) [![Cybersecurity for Beginners](https://img.shields.io/badge/Cybersecurity%20for%20Beginners-F97316?style=for-the-badge&labelColor=E5E7EB&color=F97316)](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung) [![Web Dev for Beginners](https://img.shields.io/badge/Web%20Dev%20for%20Beginners-EC4899?style=for-the-badge&labelColor=E5E7EB&color=EC4899)](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst) [![IoT for Beginners](https://img.shields.io/badge/IoT%20for%20Beginners-14B8A6?style=for-the-badge&labelColor=E5E7EB&color=14B8A6)](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst) [![XR Development for Beginners](https://img.shields.io/badge/XR%20Development%20for%20Beginners-38BDF8?style=for-the-badge&labelColor=E5E7EB&color=38BDF8)](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst) --- ### Copilot Series [![Copilot for AI Paired Programming](https://img.shields.io/badge/Copilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst) [![Copilot for C#/.NET](https://img.shields.io/badge/Copilot%20for%20C%23/.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst) [![Copilot Adventure](https://img.shields.io/badge/Copilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst) ## Getting Help If you dey jam problem or get question about how to build AI apps. Join other learners and beta developers dem for talks about MCP. Na supportive community wey questions dey welcome and knowledge dey share freely. [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) If you get product feedback or errors while you dey build visit: [![Microsoft Foundry Developer Forum](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) --- **Disclaimer**: Dis document dem translate am wit AI translation service [Co-op Translator](https://github.com/Azure/co-op-translator). Even though we dey try make am correct, abeg sabi say automated translation fit get some errors or wahala. Di original document wey dey dia for e own language na im be di main correct source. If na serious matter, better make person wey sabi language translate am. We no go take any blame if person no understand or misunderstand tins because of dis translation.