发现data science & ml类别的 Claude 技能。浏览 61 个技能,找到适合您 AI 工作流程的完美功能。
Architects scalable AI memory systems with optimized retention, storage backends, and multi-level context patterns.
Implements production-ready RAG pipelines and advanced retrieval strategies using LlamaIndex templates and scripts.
Automatically selects and executes the optimal forecasting engine between StatsForecast and TimeGPT based on your data's unique characteristics.
Architects sophisticated LLM applications using LangChain patterns for autonomous agents, conversational memory, and complex workflow orchestration.
Generates plain-English narratives and executive summaries from TimeGPT forecast results to bridge the gap between data science and business stakeholders.
Master advanced vector database operations, including distributed QUIC synchronization and hybrid search for high-performance AI applications.
Architects and implements sophisticated LLM applications using the LangChain framework for agents, memory management, and complex AI workflows.
Automates the creation, selection, and transformation of data features to optimize machine learning model performance.
Streamlines the integration and testing of Gemma 3 270M models within the Claude Code environment.
Integrates ElevenLabs Scribe v1 for high-accuracy speech-to-text transcription across 99 languages with speaker diarization.
Builds professional investment banking-grade discounted cash flow (DCF) valuation models in Excel with automated financial projections and sensitivity analysis.
Extracts text, tables, and metadata from PDF, DOCX, and HTML documents to power RAG pipelines and data processing workflows.
Implements and optimizes advanced search strategies including semantic, hybrid, and reranking for high-performance RAG systems.
Tracks and manages AI/ML model versions, lineage, and performance metrics within your development workflow.
Implements comprehensive evaluation frameworks for LLM applications using automated metrics, human feedback, and systematic benchmarking.
Implements high-performance Retrieval Augmented Generation (RAG) pipelines including document chunking, vector database integration, and semantic search.
Automates financial budget vs. actual variance analysis in Excel with professional reporting, materiality flagging, and executive summaries.
Designs and implements sophisticated LLM applications using LangChain's framework for agents, memory, and complex workflows.
Implements sophisticated autonomous agent architectures and workflow patterns using the Vercel AI SDK.
Implements advanced prompt engineering techniques to optimize LLM performance, reliability, and structured output in production environments.
Automates comprehensive AI model evaluation benchmarks to measure efficiency, code quality, and workflow adherence.
Manages complex Excel workbooks with automated formula recalculation, professional financial modeling standards, and deep data analysis capabilities.
Manages and automates complex text transformation pipelines via the TextCleaner REPL interface.
Implements end-to-end Retrieval-Augmented Generation workflows to enable accurate AI querying of specialized documentation and technical textbooks.
Builds advanced Retrieval-Augmented Generation (RAG) systems to ground LLM responses with external document knowledge and vector search.
Architects and implements sophisticated LLM applications using LangChain for agents, memory management, and complex workflows.
Optimizes Large Language Model performance through advanced prompting techniques like few-shot learning and chain-of-thought reasoning.
Optimizes neural network performance by automatically applying advanced training algorithms, learning rate schedules, and regularization techniques.
Transforms prediction market datasets into standardized Nixtla formats for seamless time-series forecasting.
Provides deep interpretability for machine learning models using SHAP and LIME to explain predictions and feature importance.
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