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Source channel @githubtrending · Post #14717 · May 18

#jupyter_notebook Learning about Large Language Models (LLMs) can be very beneficial. You can build exciting projects over eight weeks, starting with simple tasks and moving to more complex ones. This journey helps you develop deep expertise in AI and LLMs. You'll learn by doing hands-on projects, which is a fun and effective way to understand how these models work. By the end, you'll have skills that can be used in real-world applications, making it a valuable learning experience. https://github.com/ed-donner/llm_engineering

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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