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Source channel @githubtrending · Post #14993 · Jul 24

#jupyter_notebook Retrieval Augmented Generation (RAG) helps large language models (LLMs) answer questions using up-to-date or private information by connecting them to external data sources, unlike fine-tuning which retrains the model on specific data. RAG is useful when you need current, dynamic information without costly retraining, making it ideal for tasks like customer support or knowledge management. Fine-tuning is better for deep expertise in a specialized field but requires more data and effort. Using RAG lets you get accurate, relevant answers quickly by combining the model’s language skills with fresh, specific data, improving usefulness and reliability. https://github.com/langchain-ai/rag-from-scratch

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Venture Village Wall 🦄

@venturevillagewall · Post #4089 · 02/07/2025, 10:00 AM

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Property Market Thrives on Digital Platforms 📊 A study by РЭУ im. G.V. Plekhanov reveals a surge in property transactions via Циан, with nearly 500,000 families improving their housing conditions in 2024. Digital platforms are revolutionizing real estate, streamlining deals, and saving users time and money. Циан's valuation service received 14.8 million unique requests in 2024 alone. The company's IT sector now accounts for 54% of its revenue, reflecting a 171% increase since 2019. 🔗Read more #RealEstate#Циан#MarketTrends#DigitalTransformation#HousingMarket#PropertyTech#Investment#TechInnovation#RevenueGrowth#UserExperience#CostSavings#Efficiency#BusinessIntelligence#RealEstateTech#DigitalPlatforms#DataAnalysis#MarketResearch#2024Trends#Technology#PropertyEvaluation