Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Implements real-time machine learning architectures for processing unbounded data streams with sub-100ms prediction latency.
Validates hypotheses and scientific theories by ensuring they are testable and capable of being proven false through rigorous experimentation.
Implements real-time machine learning prediction patterns for high-throughput data streams with sub-second latency.
Models complex system dynamics using stocks, flows, and feedback loops to quantitatively predict behavior and test policy interventions.
Analyzes and applies Gaussian statistical patterns to data for improved prediction, quality control, and anomaly detection.
Refines confidence in hypotheses and technical decisions by systematically weighting prior beliefs against new evidence.
Prevents flawed decision-making by identifying and debunking illusory patterns or spurious correlations in data and observations.
Processes and prepares data files for AI agent testing and deployment workflows.
Extracts structured research data from academic papers and integrates it into a persistent knowledge graph.
Programmatically creates, edits, and optimizes Jupyter and Google Colab notebooks with precise JSON formatting and metadata management.
Manages complex Excel workbooks with automated formula creation, financial modeling standards, and data analysis.
Extracts structured training pairs from academic peer reviews and source documents to build high-quality datasets for LLM fine-tuning.
Performs systematic qualitative thematic analysis on document collections to extract deep structural insights and categorized themes.
Conducts comprehensive multi-paper literature reviews with deep gap analysis and automated citation mapping.
Develops production-grade Python code with a focus on type safety, fail-fast logic, and rigorous testing for research environments.
Performs hypothesis-driven statistical analysis and data visualization on datasets, system metrics, and experiment logs.
Build and deploy production-ready multi-agent systems with MCP integration and automated workflows.
Automates multi-stage research idea generation and evaluation using graph-guided search and tournament-style ranking.
Optimizes multi-agent AI systems through intelligent coordination, performance profiling, and cost-aware orchestration.
Automates the creation of production-grade Pegasus scientific workflows from high-level pipeline descriptions.
Visualizes solar observation data, EUV imagery, and machine learning model outputs using SunPy and Matplotlib.
Transforms raw SDO/AIA solar observation data into standardized, ML-ready formats through automated calibration and registration pipelines.
Enables Claude to interactively explore, analyze, and modify open Microsoft Excel workbooks using natural language commands.
Develops and deploys deep learning models for solar physics using preprocessed Sun and Space Weather data.
Converts Snakemake and Nextflow pipelines into robust Pegasus workflows for high-performance computing environments.
Downloads solar observation data from SDO, STEREO, and Solar Orbiter missions for scientific analysis and machine learning.
Establishes rigorous and defensible ground truth labels for evaluation datasets based on authoritative guidelines.
Performs advanced mathematical physics computations, symbolic algebra, and automated theorem proving using the Theory2 suite.
Conducts deep technical research and provides implementation guidance for AI-enabled software development including RAG, agentic workflows, and LLM architectures.
Integrates high-performance inference and LoRA fine-tuning for 100+ open-source LLMs via OpenAI-compatible APIs and the firectl CLI.
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