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Prompts for building AI/ML systems — RAG pipelines, model selection, prompt engineering, LLM fine-tuning, agent workflows, and responsible AI practices.
17 Prompts gefunden
Framework-driven prompt that recommends a model family and baseline for any new ML problem.
End-to-end RAG pipeline design; chunking, embedding, retrieval, rerank, generation, eval.
Generate 25 candidate features with hypotheses for a tabular ML problem.
Design an evaluation harness with a rubric and 50 diverse test cases for an LLM chatbot.
Produce a complete model card suitable for governance and compliance review.
Implement semantic search using embeddings — vector database setup, embedding generation, hybrid search, and r...
Build an AI chatbot with tool/function calling, conversation memory, RAG context, and multi-turn reasoning cap...
Build a framework to evaluate LLM outputs — accuracy, relevance, safety, cost, latency, and A/B comparison tes...
Design a multi-agent AI system — agent roles, communication patterns, task decomposition, and human-in-the-loo...
Design a production-grade Retrieval-Augmented Generation pipeline — from document ingestion and chunking strat...
Get an expert recommendation on which ML model to use for your specific problem — with trade-off analysis, bas...
Design and implement an AI agent system with tool use, memory, planning, and error recovery — using LangChain,...
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