#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag
Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data.
https://github.com/FareedKhan-dev/all-rag-techniques
#mdx
This free interactive course teaches Product Managers to use Claude Code for daily tasks like processing notes, writing PRDs, analyzing data, and strategy planning through hands-on modules (4-6 hours). Clone the repo, run `claude`, and follow guided lessons with agents and file tools—no setup needed yet. You'll work faster, get instant multi-perspective feedback, and boost productivity without quality loss.
https://github.com/carlvellotti/claude-code-pm-course
#MDX result
1 and 2 target achieved in just 1 house 21 minutes ✅
One more huge quick profit 11%🤑💰🤑
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#MDX bounced back from the Trendline on 6H Time frame,we expect a good bullish momentum from the Green zone,send it to the moon 🚀
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