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Source channel @githubtrending · Post #14909 · Jul 3

#other#agent#llm#rag Happy-LLM is a free, open-source learning project that helps you deeply understand large language models (LLMs) from basics to advanced training and applications. It teaches you key concepts like NLP, Transformer architecture, pretraining, and how to build and train your own LLaMA2 model step-by-step. You also learn practical skills like fine-tuning and using cutting-edge techniques such as Retrieval-Augmented Generation (RAG) and intelligent agents. This project is ideal if you know some Python and deep learning, and it offers both theory and hands-on code to help you master LLM development and apply it in real-world AI tasks. This can boost your skills and confidence in AI model building and research. https://github.com/datawhalechina/happy-llm

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Google Facts™ [ ️@googlefactss🌎]

@googlefactss · Post #40776 · 03/11/2026, 11:01 PM

During World War II, engineers studied planes that returned from missions. They first thought the areas with the most bullet holes needed armor. Statistician Abraham Wald realized this was survivorship bias. Survivorship bias happens when you focus only on survivors and ignore failures.The undamaged areas on returning planes were actually the critical spots. Planes hit there did not survive. He recommended reinforcing those undamaged areas. ✈️📊🛡️ [Read more] @googlefactss #SurvivorshipBias#WWII#AbrahamWald#Planes#Statistics#History