Data Science & ML Claude 技能

Replicate API Integration

Integrates the Replicate API for seamless deployment and execution of generative AI models like Flux, SDXL, and custom LoRA weights.

RAG Implementation & Semantic Search

Implements Retrieval-Augmented Generation (RAG) systems to ground LLM responses in external knowledge bases and private documents.

Similarity Search Patterns

Implements efficient semantic search and vector database patterns for RAG and recommendation systems.

Vector Index Performance Tuning

Optimizes vector database performance by tuning HNSW parameters, quantization strategies, and memory usage for efficient AI applications.

Spreadsheet Automation & Analysis

Automates the creation, editing, and professional analysis of spreadsheets using Python-based tools while preserving complex formulas and layouts.

Audio Transcription & Diarization

Transcribes audio and video files into text or structured JSON with advanced speaker diarization and voice identification.

Market Sizing & Opportunity Analysis

Calculates TAM, SAM, and SOM using professional methodologies to quantify market opportunities for startups and new business ventures.

AI Configuration & MCP Cheat Sheet

Provides standardized configuration patterns for Gemini models, Codex environments, and Model Context Protocol (MCP) servers.

LangChain Application Architecture

Architects sophisticated LLM applications using LangChain's framework for agents, memory management, and complex tool integration.

Hybrid Search Implementation

Implements advanced search architectures by combining vector similarity and keyword-based retrieval for improved RAG system recall.

LLM Performance Evaluation

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

Data Storytelling Analytics

Transforms raw business data into compelling narratives and persuasive executive presentations using proven storytelling frameworks.

AI Engineer

Architects and implements production-grade LLM applications, RAG pipelines, and intelligent agent orchestrations.

Context Engineering Fundamentals

Provides foundational strategies for managing AI agent context windows, attention mechanics, and token usage to improve model performance.

LLM Project Development Methodology

Guides the end-to-end lifecycle of LLM projects, from evaluating task-model fit to architecting resilient, agent-assisted data pipelines.

Memory Systems Design

Implements sophisticated memory architectures for AI agents to persist state, build knowledge graphs, and maintain long-term context.

BDI Mental State Modeling

Transforms external RDF context into agent mental states to enable deliberative reasoning and explainable AI within cognitive architectures.

NCBI Gene Database Explorer

Queries and retrieves comprehensive gene information from NCBI databases for genomic research and functional analysis.

GEO Database Explorer

Accesses and analyzes functional genomics data from the NCBI Gene Expression Omnibus (GEO) repository.

PathML Pathology Toolkit

Analyzes whole-slide pathology images and multiparametric imaging data using a comprehensive computational pathology toolkit.

TorchDrug Molecular Science

Accelerates drug discovery and molecular research using graph neural networks and PyTorch-based machine learning.

Arboreto Gene Regulatory Network Inference

Infers gene regulatory networks from transcriptomics data using scalable algorithms like GRNBoost2 and GENIE3.

PyDESeq2 Bioinformatics Analysis

Performs differential gene expression analysis on bulk RNA-seq data using the DESeq2 framework within Python.

Biopython Bioinformatics Toolkit

Automates computational molecular biology tasks including sequence manipulation, NCBI database queries, and structural analysis.

Single-Cell Omics Analysis (scvi-tools)

Analyzes single-cell omics data using deep generative models for batch correction, multimodal integration, and differential expression.

Hypogenic Scientific Discovery

Automates the generation and testing of scientific hypotheses by synthesizing empirical data and existing research literature.

Vaex Big Data Analysis

Processes and visualizes massive tabular datasets exceeding available RAM using high-performance out-of-core DataFrame operations.

Astropy Scientific Computing

Performs advanced astronomical data analysis, coordinate transformations, and cosmological calculations using the core Astropy Python library.

Matchms Mass Spectrometry Analysis

Processes and analyzes mass spectrometry data through spectral similarity, metadata harmonization, and automated workflows.

Cosmic Cancer Database Integration

Accesses and manages somatic mutation data from the COSMIC database for cancer research and precision oncology.