Data Science & ML Habilidades de Claude

Python Performance Optimization

Optimizes Python codebases through systematic profiling, algorithmic efficiency, and advanced acceleration techniques.

Three-Match SAT Solver Gadgets

Implements 3-SAT reductions via colored subgraph isomorphism and non-backtracking geodesics for topological computing.

Cognitive Superposition

Synthesizes category theory, compression-driven intelligence, and generative flow networks into a unified framework for advanced AI research and reasoning.

Data Processing Essentials

Streamlines data manipulation, information processing, and analytical workflows within Claude Code.

LLM Router

Routes AI requests to various LLM providers including OpenAI, Grok, Groq, and DeepSeek using the SwiftOpenAI-CLI agent mode.

Pixi Package Manager

Manages fast, reproducible scientific Python environments by unifying conda and PyPI ecosystems with multi-platform lockfile support.

AgentDB Vector Search

Implements high-performance semantic vector search for intelligent document retrieval and RAG systems using AgentDB.

Excel & Spreadsheet Automation

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

Excel & Spreadsheet Automation

Automates advanced spreadsheet creation, editing, and financial modeling with dynamic formulas and industry-standard formatting.

Tidyverse Modern R Patterns

Implements modern R programming standards using the latest tidyverse features and native pipe syntax.

Code Quality Tools for Python

Automates linting, formatting, and static type checking for scientific Python projects using Ruff, MyPy, and pre-commit hooks.

Research Analyst

Conducts systematic landscape research, competitive analysis, and evidence-based strategy evaluations to inform technical and business decisions.

Scientific Python Packaging

Standardizes the creation of distributable Python packages using modern Scientific Python community best practices and Hatchling build backends.

Modern Rlang Patterns

Implements robust R metaprogramming and tidy evaluation patterns using the rlang framework.

Data Processing Essentials

Streamlines data manipulation and analysis workflows using industry-standard Python libraries like Pandas.

Ark Agentic Framework Analysis

Analyzes the Ark (Agentic Resource Kit) codebase to provide architectural insights, source code examination, and implementation guidance for agentic applications.

CSV Data Summarizer

Analyzes CSV files automatically to generate comprehensive statistical summaries and tailored visualizations using Python and pandas.

Excel Spreadsheet Operations

Automates the creation, editing, and analysis of Excel spreadsheets with support for complex formulas and industry-standard financial modeling.

AutoRegMonkey Econometrics Agent

Automates complex econometric analysis by integrating LLM planning with RAG knowledge, Stata modeling, and Python data processing.

Runware AI Provider Integration

Automates the discovery and implementation of Runware AI image and video generation models into the CreativeEditor SDK.

Anthropic Architect

Recommends the most efficient Anthropic architecture for AI projects by analyzing requirements and selecting the optimal mix of skills, agents, and SDK primitives.

Excel & Spreadsheet Automation

Automates the creation, editing, and analysis of Excel spreadsheets with a focus on dynamic formulas and financial modeling standards.

ML Pipeline Workflow

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

Prompt Engineering Patterns

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

CSV Data Summarizer

Automates comprehensive CSV data analysis and visualization by instantly generating statistical reports and charts without requiring user prompts.

AI Agent Prompt Patterns

Provides structured patterns and best practices for crafting reliable system prompts for AI agents.

Treasure Data Agent Development

Develops and manages sophisticated LLM agents within the Treasure Data ecosystem using a YAML-based configuration workflow.

LLM Performance Evaluation

Implements systematic evaluation frameworks for LLM applications using automated metrics, human-in-the-loop feedback, and A/B testing.

LangChain Architecture Design

Architect sophisticated LLM applications using LangChain's agents, memory systems, and complex chain patterns.

RAG Implementation Guide

Builds sophisticated Retrieval-Augmented Generation systems to ground LLM responses with external knowledge and semantic search.