Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Optimizes machine learning models for production by automating quantization workflows to reduce size and increase inference speed.
Provides automated interpretability and transparency for machine learning models by explaining predictions and identifying key feature influences.
Generates production-ready Luigi tasks and complex data pipeline workflows using industry-standard orchestration patterns.
Manages API quotas and request throughput for LangChain applications using advanced rate limiting and backoff strategies.
Generates minimal, production-ready LangChain boilerplate for Python and TypeScript to jumpstart AI-powered application development.
Optimizes AI performance through advanced model routing, A/B testing, and intelligent selection strategies using the OpenRouter API.
Automates the configuration and implementation of MLflow experiment tracking for machine learning workflows.
Generates a minimal, functional Deepgram speech-to-text implementation for rapid prototyping and API testing.
Streamlines the development and orchestration of Apache Spark jobs for high-performance data pipelines.
Optimizes LangChain application performance by reducing latency, increasing throughput, and implementing efficient resource utilization patterns.
Automates the creation of production-ready TorchServe configurations for streamlined machine learning model deployment.
Automates the creation and optimization of scalable machine learning batch inference pipelines for production workloads.
Reduces and manages LLM API expenses by implementing token tracking, model routing, and advanced caching strategies within LangChain applications.
Analyzes and processes digital images using advanced object detection, classification, and segmentation techniques.
Optimizes machine learning model performance through automated feature creation, selection, and data transformation.
Calculates and interprets statistical significance for experimental data and A/B testing directly within the Claude Code environment.
Streamlines the development and optimization of Kafka-based real-time data processing applications and ETL pipelines.
Builds comprehensive conversion funnels using SQL, data visualization, and statistical analysis to optimize user journeys.
Streamlines the development of production-grade PyTorch training loops and machine learning pipelines.
Generates complex pivot tables and data summaries for business intelligence and statistical analysis.
Identifies and prevents common implementation mistakes while optimizing video generation workflows with Kling AI.
Generates interactive, production-ready Plotly visualizations and data dashboards directly within your development workflow.
Streamlines machine learning model interpretation by providing automated guidance and code for advanced explainability techniques.
Implements high-performance pre-recorded speech-to-text transcription using Deepgram’s Nova-2 AI model.
Implements automated early stopping logic to prevent model overfitting and optimize training duration in machine learning workflows.
Guides and automates the migration of LangChain applications from legacy patterns to modern standards and newer SDK versions.
Generates comprehensive cohort analysis models and SQL queries to track user behavior and retention patterns over time.
Provides comprehensive strategies and code patterns for migrating legacy LLM applications to the LangChain framework.
Automates machine learning model versioning and MLOps workflows to ensure consistent, reproducible deployment cycles.
Automates data validation and quality assurance within data pipelines to ensure accuracy and reliability.
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