{"id":15359019,"url":"https://github.com/leouieda/ml-intro","last_synced_at":"2026-02-27T21:43:51.252Z","repository":{"id":53881993,"uuid":"434479301","full_name":"leouieda/ml-intro","owner":"leouieda","description":"A very brief introduction to machine learning ","archived":false,"fork":false,"pushed_at":"2022-11-18T16:09:16.000Z","size":7247,"stargazers_count":40,"open_issues_count":4,"forks_count":3,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-19T12:32:13.652Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter 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unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-10-01T12:43:34.584Z","updated_at":"2026-02-27T21:43:51.234Z","avatar_url":"https://github.com/leouieda.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# A quick introduction to machine learning\n\n**Author:** [Leonardo Uieda](https://www.leouieda.com/)\n    \nThis is a very brief hands-on introduction to machine learning. \nIt will cover some of the common nomenclature, principles, and applications. \n\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/leouieda/ml-intro/HEAD?labpath=tutorial.ipynb)\n\n## 📓 • Jupyter Notebook\n\nThe tutorial is in the form of a Jupyter notebook (`tutorial.ipynb`). \nHere are some options for using it:\n\n* [Download the notebook](https://github.com/leouieda/ml-intro/archive/refs/heads/main.zip) and run it on your machine (**preferred**).\n* [Run it online on Binder](https://mybinder.org/v2/gh/leouieda/ml-intro/HEAD?labpath=tutorial.ipynb) which lets you try out the code and experiment but will **not save your progress**.\n* [View it online on nbviewer](https://nbviewer.org/github/leouieda/ml-intro/blob/main/tutorial.ipynb) to read the text and look at the code but not run it.\n\n## 🧑🏿‍💻 • Learner profile\n\n* Is currently in their final year of a STEM undergraduate degree or early years of a postgraduate degree.\n* Has studies the basics of statistics, Python programming, and linear algebra.\n* Is interested in using machine learning in their projects or as a future career.\n\n## 🧑‍🏫 • For instructors\n\nThe tutorial is designed to be taught as a 1-2 hour session with **live-coding**. \nTo do so, create a copy of the notebook and delete all or most of the code cells \n(it's OK to leave some in to allow more time in the tutorial). \n\nType in the code as you explain what you're doing. \nThis will help you control your pacing and avoid going too fast. \nIt also opens up the opportunity for you to make mistakes and teach students \nhow to identify and solve them.\n\nIdeally, have them follow along on their own computers, typing in the code with you.\nMake sure you also share a copy of the pre-filled notebook with students so that \nthey can choose to not type and listen at the same time.\n\n## ⚖️ • License\n\nThe original material for this tutorial can be found at [leouieda/ml-intro](https://github.com/leouieda/ml-intro).\nComments, corrections, and additions are welcome.\n\nAll Python source code is made available under the BSD 3-clause license. You\ncan freely use and modify the code, without warranty, so long as you provide\nattribution to the authors.\n\nUnless otherwise specified, all figures and Jupyter notebooks are available\nunder the [Creative Commons Attribution 4.0 License (CC-BY)](https://creativecommons.org/licenses/by/4.0/).\n\nThe full text of these licenses is provided in the [`LICENSE.txt`](LICENSE.txt)\nfile.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fleouieda%2Fml-intro","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fleouieda%2Fml-intro","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fleouieda%2Fml-intro/lists"}