发现data science & ml类别的 Claude 技能。浏览 61 个技能,找到适合您 AI 工作流程的完美功能。
Automates the creation of FiftyOne datasets from local media files and executes machine learning model inference pipelines.
Optimizes LangGraph application performance by iteratively refining prompts and node-level processing logic based on quantitative evaluation criteria.
Converts audio files into high-quality timestamped transcriptions using NVIDIA's Parakeet model optimized for Apple Silicon.
Develops predictive player projection models using specialized feature engineering and sports-specific machine learning validation techniques.
Master the foundational syntax and precision parameterization required for BUGS and JAGS statistical modeling.
Provides foundational knowledge for writing, reviewing, and optimizing high-performance Stan 2.37 Bayesian models.
Implements advanced Bayesian time series analysis using Stan and JAGS for probabilistic forecasting and state-space modeling.
Implements and optimizes hierarchical Bayesian models with support for partial pooling and advanced parameterization techniques.
Evaluates Bayesian model convergence and sampling performance using MCMC diagnostics for Stan and JAGS frameworks.
Analyzes CSV files automatically to provide statistical summaries, domain-specific insights, and relevant visualizations without requiring user intervention.
Implements the System Skill Pattern to build persistent, data-driven CLI tools that evolve through continuous user interaction.
Builds, optimizes, and executes quantum circuits and algorithms on real hardware and high-performance simulators.
Converts chemical structures into numerical representations for molecular machine learning and drug discovery workflows.
Optimizes AI agent behavior through specialized prompt engineering patterns and best practices for complex, autonomous workflows.
Facilitates seamless integration with vector databases for semantic search, retrieval-augmented generation (RAG), and high-dimensional embedding management.
Implements comprehensive evaluation frameworks to measure LLM application quality using automated metrics, human feedback, and comparative benchmarks.
Builds high-performance Retrieval-Augmented Generation (RAG) systems using vector databases and semantic search to ground LLMs in external data.
Implements advanced prompt engineering techniques to maximize LLM performance, reliability, and reasoning capabilities in production environments.
Train, deploy, and manage distributed neural networks within E2B sandboxes using the Flow Nexus ecosystem.
Implements high-performance adaptive learning and memory distillation for AI agents using the ultra-fast AgentDB vector engine.
Orchestrates multi-agent AI systems for parallel task execution and intelligent workflow coordination using dynamic topologies.
Implements high-performance, Rust-powered tokenization for training and deploying custom NLP models with speed and precision.
Provides expert guidance for building, configuring, and optimizing Retrieval-Augmented Generation (RAG) pipelines.
Generates optimized LlamaFarm configuration files from natural language descriptions for RAG and document processing workflows.
Generates vector embeddings for project-local skills and agents to enable intelligent semantic search and smart routing within Claude Code.
Enhances Claude Code with Gemini's multimodal analysis, million-token context, and real-time web search capabilities.
Automates the creation, editing, and analysis of professional Excel spreadsheets with advanced formula support and industry-standard financial modeling.
Provides expert-level GIS analysis, property lookups, and policy research for Solano County, California.
Indexes and manages multi-format reference documents to enhance RAG-based context retrieval during development tasks.
Standardizes the development of Python machine learning experiments using specific layout, execution, and asset management patterns.
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