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。
Queries and analyzes the ClinicalTrials.gov database to retrieve comprehensive trial data, patient matching information, and drug intervention research.
Constructs advanced investment models and risk assessment simulations using industry-standard DCF, Monte Carlo, and sensitivity analysis methodologies.
Streamlines the development and management of genomics pipelines on the DNAnexus cloud platform.
Integrates Benchling’s life sciences platform with Claude to automate laboratory workflows, manage biological registry entities, and sync inventory data via API.
Empowers Claude with image generation, real-time social data, and multi-model routing using autonomous micropayments.
Automates Benchling lab data management, registry entities, inventory tracking, and electronic lab notebook workflows using the Python SDK.
Accesses the COSMIC database to retrieve somatic mutations, cancer gene data, and mutational signatures for oncology research.
Automates the calculation and interpretation of key financial ratios from corporate financial statements to streamline investment analysis.
Accesses the NIH Metabolomics Workbench REST API to query metabolite data, standardized nomenclature, and experimental research studies.
Calculates and interprets key financial ratios and metrics from financial data to evaluate company performance and valuation.
Performs fast and precise arithmetic calculations using a dedicated Python-based evaluation engine.
Analyzes financial statements to calculate essential performance ratios and provide investment insights for business evaluation.
Implements production-ready machine learning pipelines for IoT monitoring, fraud detection, and document intelligence using LlamaFarm patterns.
Optimizes vector search performance by tuning HNSW parameters, quantization strategies, and search infrastructure scaling.
Detects outliers and anomalies in datasets using over 12 machine learning backends and automated training workflows.
Scaffolds production-ready RAG and document processing projects from curated LlamaFarm templates.
Select and optimize embedding models and chunking strategies for RAG, semantic search, and domain-specific vector applications.
Calculates comprehensive portfolio risk metrics and performance indicators to ensure robust capital preservation and institutional-grade risk management.
Implements high-performance similarity search and vector database patterns for RAG and semantic retrieval systems.
Designs and implements sophisticated LLM applications using LangChain's agents, memory systems, and modular chain patterns.
Builds robust, production-grade backtesting systems for trading strategies while mitigating common pitfalls like look-ahead and survivorship bias.
Implements advanced hybrid search architectures combining vector similarity and keyword matching for superior information retrieval.
Downloads Weights & Biases plots and generates comprehensive metric charts from experiment runs.
Downloads and generates high-quality metric visualizations from Weights & Biases experiment runs directly within Claude.
Implements rigorous methodological guardrails and analytical workflows for AI-assisted qualitative research projects.
Converts Markdown files into interactive Jupyter Notebooks by intelligently splitting sections and extracting code blocks.
Equips Claude with nine reinforcement learning algorithms to build self-learning agents that optimize behavior through experience and training.
Implements high-performance persistent memory and reinforcement learning patterns for stateful AI agents.
Implements an adaptive learning system that enables AI agents to recognize patterns and optimize task strategies through continuous experience.
Implement ultra-fast semantic vector search and intelligent document retrieval for RAG systems using AgentDB's high-performance HNSW indexing.
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