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Source channel @githubtrending · Post #14926 · Jul 8

#jupyter_notebook#artificial_intelligence#book#large_language_models#llm#llms#oreilly#oreilly_books You can learn how to use Large Language Models (LLMs) effectively through the book *Hands-On Large Language Models* by Jay Alammar and Maarten Grootendorst. This book uses nearly 300 custom illustrations to explain key concepts and practical tools for working with LLMs, including tokenization, transformers, prompt engineering, fine-tuning, and advanced text generation. It also provides runnable code examples in Google Colab, making it easy to practice and apply what you learn. This resource helps you understand and build your own LLM applications confidently, saving you time and effort in mastering complex AI technology. It’s highly recommended for anyone wanting hands-on experience with LLMs. https://github.com/HandsOnLLM/Hands-On-Large-Language-Models

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@emagzinewspars · Post #9464 · 11/03/2025, 03:27 AM

#The_Science🇺🇸📕[PDF]⬇️ 30 #October2025 #Weekly_Magazines For learning, for free(dom). @backupofmagazines This issue delivers a powerful special on the #MandalayEarthquake, unpacking rupture physics and how Earth’s crust defies its own limits. Seismic data, #AI-based imaging, and dual-material energy models reveal a new frontier in #Geophysics. Meanwhile, reports span #BigTech access wars, #COVID19 legacy effects, and synthetic antibodies for #Snakebite treatment. Behavioral studies highlight chimpanzee rationality and neural rewiring. Advances in #Catalysis, #Recycling, and #Neuroscience mark the rise of adaptive science facing global turbulence. From earthquakes to evolution, this issue captures the restless pulse of a changing planet. #ClimateCrisis#EarthScience#Innovation#Research