<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Scikit-Learn on Noureddine RAMDI</title><link>https://ramdi.fr/tags/scikit-learn/</link><description>Recent content in Scikit-Learn on Noureddine RAMDI</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 23 May 2026 20:41:27 +0000</lastBuildDate><atom:link href="https://ramdi.fr/tags/scikit-learn/index.xml" rel="self" type="application/rss+xml"/><item><title>A curated 100-day machine learning journey with code and resources</title><link>https://ramdi.fr/github-stars/a-curated-100-day-machine-learning-journey-with-code-and-resources/</link><pubDate>Mon, 04 May 2026 10:23:03 +0000</pubDate><guid>https://ramdi.fr/github-stars/a-curated-100-day-machine-learning-journey-with-code-and-resources/</guid><description>Explore a 100-day machine learning coding challenge combining classical algorithms, deep learning, and curated resources. A practical, day-by-day learning path for self-directed devs.</description></item><item><title>Python Data Science Handbook: Exploring the Core Python Data Science Stack Through Executable Notebooks</title><link>https://ramdi.fr/github-stars/python-data-science-handbook-exploring-the-core-python-data-science-stack-through-executable-notebooks/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/python-data-science-handbook-exploring-the-core-python-data-science-stack-through-executable-notebooks/</guid><description>Explore the Python Data Science Handbook repo offering runnable Jupyter notebooks covering NumPy, Pandas, Matplotlib, and Scikit-Learn with no local setup required.</description></item><item><title>Microsoft's ML-For-Beginners: A Project-Based Classic Machine Learning Curriculum</title><link>https://ramdi.fr/github-stars/microsoft-s-ml-for-beginners-a-project-based-classic-machine-learning-curriculum/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/microsoft-s-ml-for-beginners-a-project-based-classic-machine-learning-curriculum/</guid><description>Microsoft&amp;rsquo;s ML-For-Beginners offers a 12-week, project-based classic machine learning course using Scikit-learn and Jupyter Notebooks, focusing on foundational concepts with interactive lessons and quizzes.</description></item></channel></rss>