Data Science & ML Habilidades de Claude

Replicate AI Automation

Automates AI model inference and management on Replicate, enabling seamless integration of image, text, and audio generation into development workflows.

College Football Data Automation

Automates the retrieval and processing of college football statistics and team data using Rube MCP and Composio.

Census Bureau Automation

Automates U.S. Census Bureau data retrieval and analysis tasks through the Rube MCP and Composio toolkit.

OpenRouter Automation

Automates OpenRouter operations and AI model orchestration via the Rube MCP and Composio toolkit.

Textrazor Automation

Automates advanced natural language processing tasks including entity extraction, sentiment analysis, and topic tagging via Textrazor.

Kaggle Automation

Automates Kaggle workflows including dataset management, competition submissions, and notebook execution via Rube MCP.

Astica AI Automation

Automates computer vision, image analysis, and cognitive AI tasks directly within Claude via the Rube MCP.

Platerecognizer Automation

Automates license plate recognition and vehicle identification tasks through the Platerecognizer API and Rube MCP.

Time Series Decomposer

Decomposes complex temporal data into trend, seasonal, and residual components to uncover hidden statistical patterns.

Groq Advanced Core Workflow B

Optimizes Groq inference through batch processing, multi-model benchmarking, and systematic prompt evaluation.

OpenClaw Model Advisor

Audits OpenClaw agents to recommend the most cost-effective and capable OpenRouter models based on specific task requirements.

VideoDB AI Media Intelligence

Perceives, searches, and edits video and audio content using advanced semantic indexing and programmatic timeline tools.

Fal.ai Media Generation

Generates high-fidelity images, cinematic videos, and natural audio directly within Claude using the fal.ai MCP server.

Inventory & Demand Planning Expert

Optimizes retail inventory through advanced demand forecasting, safety stock calculations, and promotional lift analysis.

Agent Harness Construction

Optimizes AI agent architectures by designing robust action spaces, tool definitions, and error recovery protocols for higher reliability.

Cost-Aware LLM Pipeline

Optimizes LLM API expenditures through intelligent model routing, immutable budget tracking, and efficient prompt caching.

Structured Text Extraction Optimizer

Implements a hybrid decision framework to optimize text parsing by combining deterministic regex with LLM-based edge case handling.

arXiv Search & Retrieval

Searches and retrieves scientific preprints from the arXiv database for research and literature reviews.

Hugging Face Accelerate Distributed Training

Simplifies PyTorch distributed training by providing a unified API for DDP, DeepSpeed, and FSDP with minimal code changes.

PyTorch Lightning Training Framework

Simplifies PyTorch deep learning workflows by automating boilerplate, hardware management, and distributed training strategies.

ML Model Explainability & Interpretation

Provides deep insights into machine learning model predictions and feature importance using interpretability techniques like SHAP and LIME.

Bayesian Survival Analysis Models

Implements advanced Bayesian survival and time-to-event models with support for censoring and frailty effects.

Clinical Trial Multiplicity Methods

Implements and optimizes multiplicity adjustment procedures to control Family-Wise Error Rate (FWER) in clinical trial simulations.

Power Optimization Patterns for Clinical Trials

Optimizes clinical trial designs through advanced sample size determination, event count tuning, and multi-objective tradeoff analysis.

SimTrial Fundamentals

Simulates time-to-event clinical trial data and performs complex statistical analyses including weighted logrank and MaxCombo tests.

Tidy ITC Analysis Workflow

Standardizes Indirect Treatment Comparison (ITC) analyses in R using tidy modeling principles and reproducible workflow patterns.

Bayesian Time Series Modeling

Implements robust Bayesian time series models using Stan and JAGS for advanced statistical forecasting and analysis.

R Meta-Analysis Assistant

Performs comprehensive pairwise meta-analysis in R using industry-standard libraries like metafor, meta, and brms.

Tidymodels Workflow Patterns

Implements comprehensive machine learning pipelines in R using the tidymodels ecosystem, from data preprocessing to model deployment.

R Recipes Feature Engineering

Streamlines data preprocessing and feature engineering using R's Tidymodels recipes framework.