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。
Manages large-scale N-dimensional arrays with efficient chunking, compression, and cloud-native storage integration.
Manages and tracks AI/ML model versions, performance metrics, and lineage directly within the Claude Code environment.
Generates and tests scientific hypotheses automatically by combining observational data with literature insights using LLMs.
Analyzes the emotional tone of text data to classify sentiment as positive, negative, or neutral for customer feedback and social media monitoring.
Identifies unusual patterns and outliers in complex datasets using advanced machine learning algorithms.
Automates the design, configuration, and implementation of complex neural network architectures for various machine learning tasks.
Automates the creation, editing, and professional formatting of complex Excel workbooks and financial models with full formula support.
Streamlines bioinformatics pipeline development and genomics data management on the DNAnexus cloud platform.
Simplifies programmatic access to over 40 bioinformatics web services and databases using a unified Python interface.
Performs automated exploratory data analysis and generates comprehensive markdown reports for over 200 scientific file formats.
Decodes and analyzes the core architectural signals of the X recommendation engine, including SimClusters, RealGraph, and TweepCred.
Automates laboratory liquid handling workflows by generating and optimizing Opentrons Protocol API v2 scripts for Flex and OT-2 robots.
Automates end-to-end scientific research workflows from initial data analysis to publication-ready LaTeX manuscripts.
Executes complex biomedical research tasks including genomics analysis, drug discovery, and molecular biology workflows through an autonomous agent framework.
Audits machine learning models and datasets to identify biases and ensure ethical compliance through fairness metrics and mitigation strategies.
Deploy machine learning models into production environments using robust APIs, containerization, and MLOps workflows.
Accesses, downloads, and analyzes French public open data from data.gouv.fr using a specialized Python library and integrated documentation.
Discover hidden structures and anomalies in unlabeled data using advanced unsupervised learning algorithms and dimensionality reduction.
Automates deep academic research using the Perplexity Deep Research API to generate cited, evidence-based reports.
Simplifies complex data manipulation, statistical analysis, and visualization using the Python Pandas ecosystem.
Analyzes generated prompts to provide deep insights into element usage, quality comparisons, and style-based recommendations.
Synchronizes and updates the latest LLM model specifications, pricing, and API documentation automatically.
Accelerates LLM fine-tuning by 2x while reducing memory consumption by 80% for models like Llama, Mistral, and Phi.
Accesses and retrieves nucleotide sequences, raw reads, and genome assemblies from the European Nucleotide Archive (ENA) via REST APIs and FTP.
Generates optimized race-day pacing and fueling strategies tailored to individual fitness levels and specific course topography.
Accesses the Open Targets Platform to identify therapeutic targets, analyze disease associations, and evaluate drug tractability.
Analyzes Excel spreadsheets, generates pivot tables, and automates complex data visualization workflows.
Integrates with LabArchives Electronic Lab Notebook (ELN) via REST API to automate research documentation, data uploads, and notebook management.
Applies advanced statistical methods including hypothesis testing, A/B testing, and regression analysis to derive data-driven insights.
Applies rigorous statistical methods and hypothesis testing to derive data-driven insights and validate experimental results.
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