Data Science & ML Habilidades de Claude

LangChain Application Architect

Architects sophisticated LLM applications using the LangChain framework to implement agents, memory management, and complex workflow chains.

RAG Implementation Toolkit

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

Prompt Engineering Patterns

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

LLM Evaluation Framework

Implements rigorous evaluation strategies for LLM applications using automated metrics, human-in-the-loop feedback, and systematic benchmarking.

Advanced Excel & Spreadsheet Manager

Manages complex Excel workbooks with automated formula recalculation, professional financial modeling standards, and deep data analysis capabilities.

Prompt Engineering Patterns

Optimizes LLM interactions through advanced prompting techniques like few-shot learning, chain-of-thought, and systematic template design.

Agent Development Framework

Streamlines the creation, testing, and optimization of sophisticated autonomous agents and subagents within the Claude Code ecosystem.

Python Data Visualization

Generates publication-quality charts and statistical visualizations using Matplotlib and Seaborn.

Excel & Spreadsheet Automation

Automates the creation, formatting, and analysis of professional-grade Excel spreadsheets and financial models.

AgentDB Memory Patterns

Implements high-performance persistent memory and reasoning patterns for AI agents using vector storage and reinforcement learning.

ReasoningBank Intelligence

Implements adaptive learning and pattern recognition systems to enable AI agents to optimize strategies and improve through experience.

Data Analyst Export

Exports data analysis results into multiple professional formats including CSV, Excel, JSON, and Markdown with customized formatting.

Excel & Spreadsheet Master

Automates the creation, editing, and analysis of professional-grade Excel spreadsheets and financial models with dynamic formulas and rigorous verification.

TidyR Model Evaluation

Streamlines machine learning model performance assessment in R using the tidymodels ecosystem.

Complex Data Analysis

Provides a structured framework for comprehensive data processing, multi-step analysis patterns, and standardized output generation.

Advanced Excel & Spreadsheet Manager

Automates the creation, editing, and analysis of professional Excel spreadsheets with advanced formula support and industry-standard financial modeling.

Data Cleaner

Automates dataset analysis and cleaning by detecting data types, identifying quality issues, and generating Python scripts for standardized data preparation.

DBF Data Analysis & Conversion

Analyzes legacy Thai DBF accounting databases by converting them to Parquet for high-performance DuckDB querying.

Innovation Game Miner

Develops, optimizes, and submits high-performance competitive algorithms for Boolean Satisfiability, Vehicle Routing, and Knapsack challenges on The Innovation Game platform.

Behavior Tree Composer

Generates and validates executable Python behavior trees for robotic systems using natural language task descriptions.

Hugging Face Spaces Manager

Manages and interacts with Hugging Face Spaces by providing tools to search repositories, retrieve metadata, and control application runtimes.

Ollama Client

Interfaces with the Ollama API to perform high-performance text completions and clinical analysis using the Phi-4 language model.

Grail Miner Management

Optimizes the deployment, operation, and performance of Grail miners on Bittensor Subnet 81 for verifiable language model post-training.

Model Coordination

Coordinates multiple AI models in parallel to perform comparative analysis, aggregate decision-making, and track performance across diverse LLM providers.

Medallion Schema Reference

Automates schema validation and business logic extraction to ensure accuracy when generating PySpark ETL transformation code.

LLM Evaluation & Benchmarking

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

Prompt Engineering Patterns

Implements advanced LLM prompt engineering techniques to maximize model performance, reliability, and controllability in production applications.

LangChain Architecture

Builds sophisticated LLM applications using LangChain's agents, memory management, and complex chain patterns.

MLOps Pipeline Workflow

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

RAG Implementation & Vector Search

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