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。
Provides strategic guidance and technical patterns for operationalizing machine learning models from experimentation to production deployment.
Engineers reliable, high-quality LLM outputs using advanced techniques like few-shot learning, chain-of-thought reasoning, and structured data patterns.
Deploys and optimizes LLM and machine learning models for production-grade inference and API integration.
Automates quality control workflows for single-cell RNA-seq data using scverse best practices and MAD-based outlier detection.
Generates comprehensive clinical trial protocols for medical devices and drugs using a structured, research-driven automated workflow.
Automates the deployment and execution of nf-core bioinformatics pipelines for genomics, transcriptomics, and epigenomics data analysis.
Converts diverse laboratory instrument files into standardized Allotrope Simple Model (ASM) format for LIMS and data analysis.
Automates the deployment and management of nf-core bioinformatics pipelines for large-scale genomic data analysis.
Accelerates single-cell genomics research using probabilistic deep learning models for data integration, multi-modal analysis, and reference mapping.
Streamlines single-cell genomics workflows using scvi-tools for probabilistic data integration and deep learning analysis.
Converts laboratory instrument data into standardized Allotrope Simple Model (ASM) formats for LIMS integration and data analysis.
Guides scientists through a systematic framework for research problem selection, project ideation, and strategic decision-making.
Performs automated quality control and filtering on single-cell RNA-seq data using scverse best practices.
Automates the development, backtesting, and execution of Taiwan stock market quantitative trading strategies using the FinLab package.
Detects and corrects spelling errors in ETL metadata and snapshot files using codespell.
Transforms external RDF context into formal Belief-Desire-Intention (BDI) mental states for advanced cognitive agent reasoning.
Implements best practices for designing, documenting, and analyzing reproducible scientific experiments within data science workflows.
Implements rigorous data exploration, statistical testing, and scientific validation patterns using Python's data science stack.
Enforces machine learning best practices including baseline comparisons, cross-validation, model interpretation, and data leakage prevention.
Enforces scientific best practices in machine learning pipelines through baseline comparison, cross-validation, and model interpretation.
Implements best practices for designing reproducible, statistically valid scientific experiments and machine learning workflows.
Implements rigorous data exploration and statistical testing patterns for scientific research and analysis.
Builds sophisticated React chat interfaces and AI-powered components using Vercel AI SDK v6 stable patterns.
Build and deploy sophisticated AI agent workflows featuring multi-agent handoffs, realtime voice, and type-safe tool execution.
Builds advanced backend AI applications using the latest Vercel AI SDK features, including structured outputs, multi-modal capabilities, and performance optimizations.
Implements Group Relative Policy Optimization (GRPO) to fine-tune vision-language models on small, specialized datasets.
Builds stateful, agentic AI applications using OpenAI's Responses API with preserved reasoning and server-side tool integration.
Implements fully managed Retrieval-Augmented Generation (RAG) using Google Gemini for searchable document knowledge bases.
Builds and manages production-ready conversational AI voice agents with integrated ASR, TTS, and custom RAG knowledge bases.
Implements high-performance text embeddings for RAG, semantic search, and document clustering using the Google Gemini API.
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