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。
Optimizes AI models for resource-constrained edge devices using advanced quantization, memory management, and battery-smart inference patterns.
Integrates Qdrant vector database with Java applications using Spring Boot and LangChain4j for high-performance semantic search and RAG.
Performs rigorous statistical analysis, hypothesis testing, and APA-compliant reporting for academic and experimental research.
Queries and analyzes the OpenAlex database to search scholarly literature, track citations, and perform bibliometric analysis.
Provides a unified interface for rapid bioinformatics queries across 20+ genomic databases including Ensembl, AlphaFold, and NCBI.
Facilitates computational molecular biology tasks including sequence manipulation, NCBI database access, and structural bioinformatics analysis.
Trains and deploys complex neural network architectures within distributed E2B sandbox environments using Flow Nexus.
Designs and implements autonomous AI agents with sophisticated tool use, memory systems, and multi-agent orchestration.
Architects and implements robust autonomous AI agents with sophisticated tool use, memory systems, and multi-agent orchestration.
Designs adaptive user-facing agent experts to create personalized product experiences and dynamic UX.
Automates end-to-end scientific research workflows from initial data analysis and hypothesis generation to publication-ready LaTeX manuscripts.
Automates professional Excel spreadsheet creation, financial modeling, and data analysis with error-free formula verification.
Conducts comprehensive market analysis, industry trend tracking, and market sizing calculations to drive data-informed business decisions.
Enables programmatic PDF manipulation, data extraction, and document creation using professional Python and command-line tools.
Performs high-performance genomic interval analysis, overlap detection, and machine learning tokenization using Rust-powered tools.
Manages large-scale scientific dataset transfers between remote Globus endpoints and high-performance computing clusters.
Enhances multiplex immunofluorescence images by applying range-specific weights to remove background noise while preserving delicate biological signals.
Performs robust differential gene expression analysis for bulk RNA-seq data using the Python implementation of DESeq2.
Corrects multi-action trading logic bugs and optimizes backtesting notebooks for Google Colab environments.
Optimizes KINTSUGI batch processing by enforcing GPU-only SLURM scheduling to achieve up to 25x speedups over CPU fallback.
Implements granular skip-existing checks in Snakemake wrapper scripts to resume interrupted HPC jobs without re-processing completed channels.
Performs comprehensive biological data analysis, including sequence manipulation, phylogenetics, and microbiome ecology statistics.
Integrates the Google Gemini CLI into Claude to provide large-context analysis, safe sandbox execution, and structured code modifications.
Generates testable, evidence-based scientific hypotheses and experimental designs across multiple research domains.
Evaluates scientific research rigor by assessing methodology, statistical validity, and bias through established frameworks like GRADE and Cochrane ROB.
Accelerates drug discovery and molecular modeling using graph neural networks and curated biological datasets within PyTorch.
Accesses and analyzes global public statistical data through the Data Commons knowledge graph and Python API.
Generates comprehensive, 50+ page professional market research reports with consulting-grade analysis and high-fidelity visualizations.
Facilitates programmatic access to over 61 million standardized single-cell genomics data points for advanced querying and analysis.
Analyzes single-cell RNA-seq data with standardized workflows for quality control, clustering, and cell type annotation.
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