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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 #9391 · 10/21/2025, 08:58 AM

#The_Science🇺🇸📕[PDF]⬇️ 16 #October2025 #Weekly_Magazines For learning, for free(dom). @backupofmagazines This week’s Science dives deep into the frontiers of #Nanoscopy, visualizing neural circuits with stunning 3D precision. From Arctic #Permafrost preserving ancient RNA viruses to #Ant colonies evolving architectural immunity, the issue spans from the microscopic to the planetary. Groundbreaking work tracks #SeaLevel change over 4.5 million years and explores durable #Hydrogen production membranes and electric control in #2Dmaterials. The “#ColdStorage” feature warns of hidden viral archives in melting ice—a chilling insight into #ClimateScience and future pandemics. A visionary issue linking biology, chemistry, and global sustainability through the lens of innovation.