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Source channel @githubtrending · Post #14869 · Jun 26

#html#data_science#education#machine_learning#machine_learning_algorithms#machinelearning#machinelearning_python#microsoft_for_beginners#ml#python#r#scikit_learn#scikit_learn_python Microsoft’s "Machine Learning for Beginners" is a free, 12-week course with 26 lessons designed to teach classic machine learning using Python and Scikit-learn. It includes quizzes, projects, and assignments to help you learn by doing, with lessons themed around global cultures to keep it engaging. You can access solutions, videos, and even R language versions. The course is beginner-friendly, flexible, and helps build practical skills step-by-step, making it easier to understand and apply machine learning concepts in real-world scenarios. This structured approach boosts your learning retention and prepares you for further study or career growth in ML[1][5]. https://github.com/microsoft/ML-For-Beginners

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Новая работа регулярного выпуска👇 🟢 2022 🟢 V. 9 🟢 Issue 4 🟢 No. 20229415🟢 Letter 📜 Local structure and ionic transport in acceptor-doped layered perovskite BaLa2In2O7 👩‍🎓 Nataliia A. Tarasova (https://orcid.org/0000-0001-7800-0172) 🏛 Institute of High Temperature Electrochemistry UB RAS, http://www.ihte.uran.ru 📚#layered_perovskite#ionic#conductivity#acceptor_doping#BaLa2In2O7 🔗https://doi.org/10.15826/chimtech.2022.9.4.15 https://journals.urfu.ru/index.php/chimtech/article/view/6272

Новая работа регулярного выпуска👇 🟢 2022 🟢 V. 9 🟢 Issue 4 🟢 No. 20229405🟢 📜 Phosphorus-doped protonic conductors based on BaLanInnO3n+1 (n = 1, 2): applying oxyanion doping strategy to the layered perovskite structure 👩‍🎓👨‍🎓 N. Tarasova (https://orcid.org/0000-0001-7800-0172), A. Galisheva (https://orcid.org/0000-0003-4346-5644) 🏛 Institute of High Temperature Electrochemistry, http://www.ihte.uran.ru 📚#layered#perovskite#oxyanion#doping#proton#conductivity#BaLaInO4#BaLa2In2O7 🔗https://doi.org/10.15826/chimtech.2022.9.4.05 https://journals.urfu.ru/index.php/chimtech/article/view/5979