Data Science & ML Habilidades de Claude

LLM Integration & Chat Completions

Implements advanced large language model chat completions and conversational context management using the z-ai-web-dev-sdk.

Trading Performance Analysis

Analyzes Interactive Brokers CSV statements to uncover trading edges, identify risk management patterns, and generate professional performance reports.

Hypothesis Testing Framework

Guides users through a scientifically rigorous five-phase hypothesis testing process to eliminate bias and p-hacking in data analysis.

AI/ML Integration

Integrates cutting-edge AI and machine learning capabilities into applications using LLM APIs, vector databases, and RAG architectures.

Run-Smart AI Skill Registry

Manages the discovery, safety guardrails, and shared contracts for Run-Smart AI coaching skills.

Functional Introspection Principle

Applies structured self-analysis and governance protocols to evaluate and validate AI decision-making processes.

Kymera Mean-Reversion Optimizer

Optimizes mean-reversion trading strategy parameters through real-time performance analysis and pattern identification.

IRP Embodiment Framework

Connects Claude's cognitive orchestration to physical robotics and sensor systems using low-latency control and cryptographic integrity.

Implement Paper From Scratch

Guides the step-by-step implementation of research papers from scratch to ensure deep understanding and technical reproducibility.

Claude Opus 4.5 Migration Guide

Migrates codebases and prompts from legacy Claude models to Opus 4.5 across various API platforms.

Prompt Optimizer for AI & ML

Refines and compresses LLM prompts to minimize token usage, lower operational costs, and maximize response quality.

Kokoro Local Text-to-Speech

Converts text and long-form markdown documents into high-quality audio locally using the Kokoro-82M model optimized for Apple Silicon.

AI Prompt Engineering & Optimization

Optimizes LLM prompts to minimize token usage, reduce operational costs, and enhance model response quality through automated refinement.

Research Taste Developer

Develops the analytical intuition to distinguish high-impact, foundational research from incremental work and academic noise.

UMAP-Learn Dimensionality Reduction

Performs high-performance nonlinear dimensionality reduction for data visualization, clustering preprocessing, and supervised manifold learning.

Sentiment Analysis Tool

Analyzes text data to identify emotional tone and classify sentiment as positive, negative, or neutral.

Prompt Engineer

Engineers and optimizes high-quality LLM prompts across multiple models using established best practices and systematic refinement techniques.

Value Pluralism Resolver

Resolves conflicts between competing ethical and technical values through a structured pluralistic analysis framework.

NLP Text Analyzer

Analyzes textual data to extract sentiments, keywords, and core topics using advanced natural language processing techniques.

Civitai Video Performance Analyst

Analyzes Civitai video engagement and content metrics through natural language SQL queries and automated reporting.

Clustering Algorithm Runner

Executes sophisticated clustering algorithms on datasets to uncover hidden patterns, identify data groupings, and detect anomalies.

Clustering Algorithm Runner

Executes machine learning clustering algorithms to identify patterns, groups, and anomalies within complex datasets.

Cosmic Cancer Database Access

Access and query the COSMIC database for somatic mutations, cancer gene census, and mutational signatures to support precision oncology research.

Data Visualization Creator

Generates professional data visualizations, charts, and graphs from raw datasets to uncover patterns and insights automatically.

Data Visualization Creator

Transforms raw datasets into informative and visually compelling charts, plots, and graphs using intelligent automated selection.

PathML Computational Pathology

Analyzes whole-slide pathology images and multiparametric imaging data using advanced machine learning and spatial graph techniques.

Phylogenetic Tree Analysis (ETE)

Manipulates, analyzes, and visualizes phylogenetic and hierarchical tree structures with biological database integration.

Matplotlib Visualization

Generates high-quality static, animated, and interactive visualizations for data analysis and scientific publication.

TorchDrug Science Toolkit

Provides an advanced machine learning framework for drug discovery, molecular property prediction, and protein modeling using PyTorch.

Machine Learning Model Deployment

Automates the transition of machine learning models into production-ready environments and high-performance APIs.