data science & ml向けのClaudeスキルを発見してください。61個のスキルを閲覧し、AIワークフローに最適な機能を見つけましょう。
Calculates comprehensive portfolio risk metrics and performance indicators for quantitative trading strategies and investment management.
Builds production-grade backtesting systems for trading strategies while mitigating common biases and accounting for realistic market costs.
Builds sophisticated LLM applications using the LangChain framework to implement autonomous agents, complex workflows, and persistent memory.
Optimizes vector database indexes for production performance by balancing search latency, recall accuracy, and memory consumption.
Builds production-grade Retrieval-Augmented Generation (RAG) systems using vector databases and semantic search for LLM applications.
Builds and automates end-to-end MLOps pipelines from data ingestion and preparation through model training, validation, and production deployment.
Optimizes embedding model selection and chunking strategies to improve semantic search and RAG application accuracy.
Transforms complex datasets into persuasive narratives and executive-ready presentations using proven storytelling frameworks.
Implements comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
Builds production-ready Apache Airflow DAGs using industry-standard patterns for orchestration and data engineering.
Analyzes and extracts deep insights from images, videos, and audio files using advanced AI models.
Streamlines building high-performance OLAP applications using DuckDB, MotherDuck, and Parquet in Node.js and TypeScript.
Integrates 300+ AI models into Claude Code for specialized tasks, high-fidelity image generation, and cross-model reasoning.
Builds sophisticated LLM applications and autonomous agents using the LangChain framework's core patterns and integrations.
Implements a multi-layered memory architecture based on Mem0 research to boost AI accuracy and persistence across sessions.
Enables persistent semantic search and long-term memory capabilities using Qdrant vector database for advanced RAG workflows.
Analyzes CSV files automatically to generate comprehensive statistical summaries and context-aware visualizations using Python and pandas.
Builds macro-economic models using leading and coincident indicators to automate Risk-On/Risk-Off switching strategies.
Generates realistic AI avatar lip-sync videos from a single image and audio file using the OmniHuman1 framework.
Performs comprehensive clinical trial design and statistical analysis in R, covering sample size calculation, randomization, and regulatory-compliant modeling.
Transforms raw research data into structured executive reports and technical implementation plans.
Evaluates machine learning model performance using R's yardstick and tidymodels ecosystem for robust classification and regression analysis.
Performs fast, scalable nonlinear dimensionality reduction for high-dimensional data visualization, clustering, and feature engineering.
Optimizes machine learning models using comprehensive hyperparameter tuning patterns within the R Tidymodels ecosystem.
Simplifies complex bioinformatics workflows in R using Bioconductor for RNA-seq, microarray, and single-cell genomic analysis.
Builds advanced financial models including DCF analysis, Monte Carlo simulations, and scenario planning for data-driven investment decisions.
Generates high-quality videos and animations from text or images using the Google GenAI Veo 3.1 model.
Builds and orchestrates sophisticated AI agents and multi-agent workflows using the Microsoft Agent Framework for .NET applications.
Validates speleothem-based paleoseismic research by testing cave geochemical records against modern earthquake catalogs.
Implements end-to-end machine learning pipelines in R using the tidymodels ecosystem, from data splitting to model deployment.
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