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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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@githubtrending · Post #15060 · 08/15/2025, 11:30 AM

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#python#alibabacloud#android#android_emulator#aws#azure#cloud#docker#docker_android#emulator#gcp#genymotion#jenkins#kubernetes#mobile_app#mobile_web#novnc#saltstack#selenium#selenium_grid#terraform You can use Docker-Android to run Android emulators inside Docker containers, which helps you develop and test Android apps easily without needing physical devices. It offers many device profiles like Samsung Galaxy and Nexus models, supports viewing the emulator via VNC, sharing logs through a web interface, and controlling the emulator remotely with adb. It works on Ubuntu and can integrate with cloud services like Genymotion. This setup speeds up development, testing, and automation, making your workflow more consistent and efficient while saving resources. You can also persist data and run unit or UI tests with popular frameworks like Appium and Espresso. This helps you build and test Android apps faster and more reliably. https://github.com/budtmo/docker-android