Data Science & ML Claude 技能

Data Visualization Insight

Explores datasets and generates interactive visualizations in marimo notebooks using Polars and Plotly Graph Objects.

Vector RAG GUI

Search and synthesize local vector RAG stores using an AI-powered graphical interface.

Flow Nexus Neural

Deploys and trains sophisticated neural networks across distributed sandbox environments using various architectures and federated learning techniques.

Memory Leak Detector

Identifies and resolves memory exhaustion issues in Python and PyTorch applications, specifically targeting matplotlib figures and tensor accumulation.

Architecture Reviewer

Enforces adherence to PRISM architectural patterns by validating the implementation of Runner and Trainer classes during refactoring.

Marimo Reactive Notebook Development

Builds reactive Python notebooks and interactive data applications using marimo's directed acyclic graph (DAG) execution model.

Medical Diagnosis

Assists medical professionals by extracting symptoms from natural language, identifying potential diagnoses, and suggesting clinical next steps.

ReasoningBank Intelligence

Implements adaptive learning systems to enable AI agents to recognize patterns, optimize strategies, and improve continuously through experience.

Data Ingestion Builder

Automates the creation of robust data ingestion providers using standardized patterns for registry mapping, storage abstraction, and metadata tracking.

LLM Performance Evaluation

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

Analyze Goodreads Export

Queries and analyzes personal book libraries from Goodreads CSV exports to provide reading insights and statistics.

ML Pipeline Workflow

Builds and orchestrates end-to-end MLOps pipelines from data preparation and model training to production deployment.

RAG Implementation Guide

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

Prompt Engineering Patterns

Implement advanced LLM prompting techniques like few-shot learning and chain-of-thought to enhance production AI reliability and output quality.

Prompt Engineering Patterns

Optimizes LLM performance and reliability through advanced techniques like few-shot learning, chain-of-thought reasoning, and modular prompt templates.

RAG Implementation for LLM Apps

Builds high-performance Retrieval-Augmented Generation systems using vector databases and semantic search to ground AI responses in external knowledge.

LangChain Architecture & Agent Design

Architects sophisticated LLM applications using LangChain agents, multi-step workflows, and advanced memory management systems.

Machine Learning Pipeline Workflow

Builds and orchestrates end-to-end MLOps pipelines from data preparation and training through to production deployment.

LangGraph Fine-Tuning

Optimizes LangGraph application performance by iteratively refining prompts and node-level processing logic based on quantitative evaluation criteria.

LLM CLI

Interacts with diverse large language models through a command-line interface to perform tasks like prompt execution, data extraction, and embedding management.

Parakeet Audio Transcription

Converts audio files into high-quality timestamped transcriptions using NVIDIA's Parakeet model optimized for Apple Silicon.

Fantasy Football Analytics & ML

Develops predictive player projection models using specialized feature engineering and sports-specific machine learning validation techniques.

System Skill Source

Implements the System Skill Pattern to build persistent, data-driven CLI tools that evolve through continuous user interaction.

SpatialData

Manages, analyzes, and visualizes multi-modal spatial omics data using the SpatialData Python ecosystem and OME-NGFF standards.

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.

FTD Analysis Output Validator

Ensures the integrity of FTD analysis output by validating JSONL structures, TALD scale requirements, and clinical domain completeness.

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.