data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Automates scientific hypothesis generation and testing by combining empirical data with literature insights for accelerated research discovery.
Automates scientific hypothesis generation and testing by combining observational data with literature insights using large language models.
Streamlines computational molecular biology tasks including sequence analysis, NCBI database queries, and structural bioinformatics.
Transforms monolithic Python research code and notebooks into modular, production-ready package structures.
Generates evidence-based, testable scientific hypotheses and structured experimental designs from observations and literature data.
Processes, filters, and analyzes mass spectrometry data using the Matchms Python library for metabolomics and spectral research.
Accesses and analyzes global public statistical data from the Data Commons knowledge graph.
Enables parallel and distributed computing in Python to scale pandas, NumPy, and custom workflows for massive datasets.
Evaluates research rigor by assessing methodology, statistical validity, and bias using established frameworks like GRADE and Cochrane.
Accesses the Ensembl REST API to retrieve genomic sequences, gene annotations, and variant analysis data for over 250 species.
Analyzes and extracts deep insights from video files and YouTube URLs using the Google Gemini API.
Implements rigorous evaluation strategies for AI applications using automated metrics, human feedback, and LLM-as-judge patterns.
Orchestrates end-to-end MLOps pipelines from data preparation and model training to production deployment and monitoring.
Implement comprehensive evaluation frameworks for Large Language Model applications using automated metrics, human feedback, and LLM-as-judge patterns.
Automates video format conversion, audio extraction, and high-accuracy speech-to-text transcription using FFmpeg and Whisper.
Architects and implements robust Retrieval-Augmented Generation (RAG) systems using vector databases and semantic search to ground AI responses.
Deploys and trains neural networks in distributed E2B sandbox environments for advanced machine learning workflows.
Builds end-to-end MLOps pipelines covering data preparation, model training, validation, and production deployment.
Build robust Retrieval-Augmented Generation (RAG) systems using vector databases and semantic search to ground AI responses in external data.
Executes autonomous biomedical research tasks across genomics, drug discovery, and molecular biology using integrated databases and code execution.
Accesses and analyzes comprehensive pharmaceutical data from DrugBank for drug discovery, interaction analysis, and pharmacological research.
Orchestrates end-to-end MLOps pipelines from data preparation and model training to production deployment and monitoring.
Automates complex biomedical research tasks including genomics analysis, drug discovery, and CRISPR screening using integrated data and code execution.
Integrates Claude with the DNAnexus cloud genomics platform to develop bioinformatics apps, manage sequencing data, and orchestrate analysis workflows.
Automates the end-to-end scientific research lifecycle from data analysis and hypothesis generation to publication-ready LaTeX manuscripts.
Automates end-to-end scientific research workflows from initial data analysis to publication-ready LaTeX manuscripts.
Implements ultra-fast semantic vector search and HNSW indexing for high-performance RAG systems and intelligent document retrieval.
Analyzes single-cell RNA-seq data using Python for quality control, clustering, and cell type annotation.
Builds professional-grade financial models including DCF analysis, Monte Carlo simulations, and multi-scenario investment projections.
Parses and manages Flow Cytometry Standard (FCS) files to extract event data as NumPy arrays and handle complex metadata.
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