Data Science & ML Habilidades de Claude

Prompt Engineering Patterns

Master advanced techniques to maximize LLM performance, reliability, and controllability in production environments.

ML Pipeline Workflow

Orchestrates end-to-end MLOps pipelines from data preparation and training to validation and production deployment.

LLM Application Evaluation

Implement comprehensive evaluation frameworks for LLM applications using automated metrics, human feedback, and benchmarking.

MLOps Pipeline Workflow

Orchestrates end-to-end machine learning lifecycles from data preparation and training to production deployment and monitoring.

LangChain Architecture

Designs and implements sophisticated LLM applications using the LangChain framework with advanced patterns for agents, memory, and tool integration.

Prompt Engineering Patterns

Implements advanced prompt engineering techniques to optimize LLM performance, reliability, and controllability in production environments.

LLM Performance Evaluation

Implements comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and comparative benchmarking.

Ahling Intelligence Layer

Deploys and manages a sophisticated AI infrastructure stack including graph databases, vector search, and multi-agent orchestration.

AI Core Command Center

Deploys and manages a self-hosted AI infrastructure stack including LLM proxies, inference servers, vector databases, and observability tools.

Metabolomics Analysis

Provides expert strategies for metabolite identification, pathway enrichment, and metabolic flux analysis to interpret complex biochemical data.

AI Gateway Manager

Manages and routes requests across multiple AI providers including Anthropic, Ollama, and HuggingFace.

Creating Visualizations

Generates professional terminal-based and image-based visualizations to communicate data patterns and analytics results clearly.

Cleaning Data

Implements a systematic data quality remediation process to detect duplicates, handle outliers, and standardize inconsistencies for reliable analysis.

Data Import and Profiling

Systematizes the process of discovering, profiling, and importing CSV data into relational databases with comprehensive quality checks.

Structural Biology Analysis

Analyzes protein and molecular structures through AlphaFold interpretation, quality validation metrics, and comparative structural techniques.

Microsoft Agent Orchestrator

Orchestrates complex multi-agent systems using Microsoft AutoGen and Semantic Kernel with local LLM support.

Example Analysis Skill

Provides a standardized workflow for data preparation, exploratory analysis, and high-quality visualization using Python libraries.

Perception Pipeline

Deploys and manages advanced smart home perception layers including NVR, facial recognition, and local voice processing pipelines.

Vector RAG Tool

Indexes codebases and documents for semantic search to enable local Retrieval-Augmented Generation (RAG) using Ollama and FAISS.

Yanex Experiment Tracking

Streamlines the execution, management, and analysis of machine learning experiments using a lightweight, Git-aware Python framework.

ML Pipeline Workflow

Orchestrates end-to-end MLOps pipelines from data preparation and model training to production deployment and monitoring.

RAG Implementation Expert

Builds robust Retrieval-Augmented Generation (RAG) systems to ground LLM applications in external knowledge and proprietary data.

LLM Evaluation Framework

Implements comprehensive evaluation strategies for Large Language Model applications using automated metrics, human feedback, and comparative benchmarking.

LangChain Architecture

Builds sophisticated LLM applications and autonomous agents using the LangChain framework's core patterns and integrations.

Prompt Engineering Patterns

Implements advanced prompt engineering techniques to optimize LLM performance and output reliability for production applications.

RAG Implementation Guide

Builds sophisticated Retrieval-Augmented Generation systems to ground LLM applications with proprietary data and external knowledge.

LangChain Architecture & Agent Design

Architects sophisticated LLM applications using LangChain patterns for agents, memory management, and complex workflow orchestration.

LLM Evaluation & Metrics

Implements comprehensive evaluation frameworks for LLM applications using automated metrics, human feedback, and LLM-as-judge patterns.

ML Pipeline Workflow

Orchestrates end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment.

RAG Implementation Toolkit

Builds advanced Retrieval-Augmented Generation (RAG) systems using vector databases and semantic search to ground AI responses in proprietary data.