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。
Analyzes US fiscal deficit expansion and Treasury risk scenarios during periods of rising unemployment and high GDP growth.
Builds robust AI-powered applications using advanced prompt engineering, RAG patterns, and multi-provider LLM integrations.
Systematizes the process of discovering, profiling, and importing CSV data into relational databases with comprehensive quality checks.
Optimizes LLM performance and reliability through advanced prompting techniques like few-shot learning and chain-of-thought reasoning.
Validates AI model checkpoints against datasets to measure performance and benchmark key metrics.
Automates the discovery and retrieval of the latest research papers from arXiv across multiple scientific categories.
Systematically optimizes machine learning model performance by searching for the ideal hyperparameter configurations.
Executes and monitors neural network training runs using best-practice configurations and mandatory logging backends.
Analyzes machine learning training logs to visualize loss curves, detect training issues, and provide diagnostic insights.
Analyzes and predicts AI model performance by empirically testing relationships between model size, dataset volume, and compute budget.
Guides the creation of rigorous, well-controlled experiments for machine learning and data science projects.
Diagnoses and fixes machine learning training issues including loss plateaus, gradient instabilities, and convergence failures.
Monitors machine learning training progress in real-time by integrating with logging backends and visualization tools.
Automates the creation of standardized Climpt agent directories and configuration files to accelerate AI agent development.
Produces comprehensive, well-sourced research reports using an iterative diffusion-based refinement methodology.
Architects sophisticated LLM applications using LangChain agents, multi-step workflows, and advanced memory management systems.
Implements systematic evaluation strategies for LLM applications using automated metrics, human feedback loops, and benchmarking frameworks.
Integrates Amazon Bedrock Runtime APIs for unified model inference, streaming, and safety guardrails across multiple foundation models.
Performs complex numerical analysis and scientific computing using MATLAB and GNU Octave syntax for matrix operations and data visualization.
Optimizes Apache Spark data processing jobs through advanced partitioning, memory management, and shuffle tuning.
Quantifies and validates the long-cycle transmission relationship between Platinum futures and the Brazilian stock market (EWZ) using statistical cross-correlation.
Detects historical extremes in US equity valuations by normalizing metrics like CAPE and PE into percentile scores.
Empowers Claude to perform statistical modeling, design experiments, and build predictive machine learning pipelines using Python.
Implements comprehensive evaluation frameworks for LLM applications using automated metrics, human feedback, and LLM-as-judge patterns.
Validates the ethical implications, fairness, and potential biases of AI models and datasets to ensure responsible development.
Analyzes AI models and datasets to identify biases, evaluate fairness metrics, and ensure responsible AI development.
Refines and compresses LLM prompts to minimize token usage, reduce costs, and maximize output quality.
Optimizes LLM prompts to reduce token usage, lower operational costs, and improve response performance.
Orchestrates complex multi-agent systems and intelligent task routing using the AI SDK v5 across multiple LLM providers.
Orchestrates sophisticated multi-agent systems using the AI SDK v5 to manage agent handoffs, task routing, and complex collaborative workflows.
Scroll for more results...