data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Extends Transformer model context windows using RoPE, YaRN, and ALiBi techniques for processing massive documents and datasets.
Optimizes Claude's outputs and debugging capabilities using Anthropic's official prompt engineering best practices and techniques.
Streamlines the development of type-safe AI agents using the Pydantic AI framework for Python.
Provides expert guidance and automated workflows for building, testing, and documenting R packages using industry-standard tools like devtools and roxygen2.
Routes machine learning workflows to specialized guides for deployment, optimization, MLOps tooling, and production observability.
Routes PyTorch engineering challenges to specialized domain experts based on specific symptoms, performance bottlenecks, and implementation requirements.
Manages and analyzes labeled multidimensional arrays for complex scientific data workflows using Xarray.
Synchronizes MetaTrader 5 and Python environments to automate market data exports and translate MQL5 indicators into validated Python code.
Simplifies the development and deployment of complex AI agents and multi-agent workflows using the LangGraph-based Deep Agents framework.
Routes reinforcement learning problems to specialized algorithms and implementation strategies based on task characteristics and environmental constraints.
Guides and routes LLM-related development tasks toward specialized patterns for prompt engineering, RAG, fine-tuning, and model optimization.
Provides expert guidance for writing high-performance Stan probabilistic programming models and integrating them with R or Python workflows.
Performs constraint-based metabolic modeling and systems biology simulations to analyze cellular metabolism and phenotype predictions.
Implements high-performance, privacy-focused speech recognition systems using Faster Whisper for secure audio transcription and voice assistant integration.
Automates budget vs actual variance analysis in Excel to identify root causes and generate executive-ready financial reports.
Builds investment-grade discounted cash flow valuation models in Excel with automated projections and sensitivity analysis.
Generates sophisticated Excel pivot tables, calculated fields, and interactive slicers for rapid data analysis and reporting.
Builds sophisticated leveraged buyout (LBO) models in Excel, complete with debt schedules and private equity return analysis.
Mines extensive decision logs to generate high-quality, structured instruction-tuning datasets for autonomous AI model training.
Provides a comprehensive reference for developing native C extensions and GCL applications within the GreyCat ecosystem.
Performs comprehensive biological pathway analysis and gene-to-pathway mapping using the Reactome open-source database.
Synthesizes fragmented research findings into coherent, structured narratives with evidence-based uncertainty quantification.
Provides a comprehensive C/C++ API reference and implementation patterns for high-performance local LLM inference using llama.cpp.
Queries and manipulates biological and medical ontologies using the powerful OAK library for complex semantic operations.
Automates the fine-tuning of Gemma 270M models using LoRA adapters for domain-specific tasks and autonomous operations.
Standardizes the scientific research process by guiding users through rigorous hypothesis formulation, experimental design, and variable mapping.
Simplifies the deployment and management of Unsloth fine-tuning jobs on Hugging Face cloud GPUs.
Manages local GPU fine-tuning workflows using Unsloth to optimize LLM training performance and resource utilization.
Generates optimized training notebooks and scripts for fine-tuning LLMs using the Unsloth framework.
Analyzes single-cell omics data using deep generative models for tasks like batch correction, integration, and differential expression.
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