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。
Validates causal inference models by performing placebo-in-time sensitivity tests to ensure detected effects are not spurious.
Accesses built-in example datasets for causal inference and quasi-experimental modeling.
Identifies and analyzes profitable cryptocurrency arbitrage opportunities across CEX, DEX, and cross-chain markets in real-time.
Analyzes and identifies the most impactful variables in machine learning models to improve interpretability and performance.
Automates the transformation, scaling, and selection of data features to optimize machine learning model performance and accuracy.
Streamlines the creation, training, and optimization of TensorFlow machine learning models with production-grade code and automated best practices.
Streamlines the process of exporting, optimizing, and deploying TensorFlow models using the industry-standard SavedModel format.
Validates cryptocurrency and traditional trading strategies against historical data to calculate risk-adjusted performance metrics.
Bootstraps minimal Lindy AI agent integrations to verify API connectivity and learn core SDK patterns.
Simplifies the development and integration of DART physics engine simulations using Python bindings.
Generates professional ROC curves and calculates AUC metrics to evaluate machine learning classification model performance.
Architects production-ready LangChain workflows using LCEL, dynamic prompt templates, and complex composition patterns.
Analyzes historical time-dependent data to predict future trends and patterns using advanced statistical models.
Generates high-quality cinematic videos from text descriptions using Kling AI's advanced generative models.
Streamlines the creation, validation, and implementation of regression models for advanced statistical data analysis.
Automates the generation and optimization of NVIDIA Triton Inference Server configurations for high-performance ML model serving.
Diagnoses and resolves common LangChain errors, exceptions, and integration issues to streamline AI application development.
Generates and optimizes production-ready Dagster data pipelines for orchestration, ETL, and data transformation workflows.
Automates the creation and optimization of data augmentation pipelines to improve machine learning model performance and robustness.
Generates a minimal, functional Deepgram speech-to-text implementation for rapid prototyping and API testing.
Calculates and interprets statistical significance for experimental data and A/B testing directly within the Claude Code environment.
Manages API quotas and request throughput for LangChain applications using advanced rate limiting and backoff strategies.
Recommends and implements the most effective data visualizations based on your dataset's structure and analytical goals.
Generates interactive, production-ready Plotly visualizations and data dashboards directly within your development workflow.
Automates the configuration and implementation of MLflow experiment tracking for machine learning workflows.
Provides comprehensive strategies and code patterns for migrating legacy LLM applications to the LangChain framework.
Implements high-performance pre-recorded speech-to-text transcription using Deepgram’s Nova-2 AI model.
Automates the implementation of robust model checkpointing strategies to ensure resilient and reproducible machine learning training workflows.
Automates machine learning model versioning and MLOps workflows to ensure consistent, reproducible deployment cycles.
Builds autonomous LangChain agents capable of tool calling and multi-step decision-making workflows.
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