Data Science & ML Claudeスキル

Machine Learning Feature Engineering

Optimizes machine learning model performance by automating feature creation, selection, and complex data transformations.

Scientific Critical Thinking

Evaluates research rigor and methodology through systematic assessment of statistical validity, biases, and evidence quality.

Model Versioning Tracker

Tracks and manages AI/ML model versions, performance metrics, and lineage for streamlined model registry management.

Excel Variance Analyzer

Automates budget vs. actual financial variance analysis with professional reporting, materiality flagging, and executive summaries.

Sentiment Analysis Tool

Analyzes and classifies the emotional tone of text data to provide insights into customer feedback, social media sentiment, and public opinion.

PyLabRobot Lab Automation

Automates laboratory workflows and controls liquid handling robots and analytical equipment through a hardware-agnostic Python interface.

Model Explainability Tool

Provides deep interpretability and explainability for machine learning models using advanced techniques like SHAP and LIME.

NetworkX Graph Analysis

Analyzes, visualizes, and manipulates complex network structures and graph data using the NetworkX Python library.

Statsmodels Statistical Analysis

Performs rigorous statistical modeling and econometric analysis using Python's statsmodels library for deep data insights.

CZ CELLxGENE Census Data Analysis

Enables programmatic access and analysis of the CZ CELLxGENE Census, a collection of over 61 million standardized single-cell genomics records.

Vaex Big Data Analysis

Processes and analyzes massive tabular datasets exceeding RAM limits using high-performance out-of-core DataFrames.

AI Recommendation Engine Builder

Builds sophisticated recommendation systems using collaborative filtering, content-based algorithms, and hybrid machine learning models.

Data Visualization Creator

Generates professional plots, charts, and graphs from raw data with intelligent, automatic visualization type selection.

Machine Learning Model Evaluation Suite

Assesses machine learning model performance using comprehensive metrics to facilitate validation, testing, and optimization workflows.

PathML Pathology Analysis

Analyzes whole-slide images and multiparametric data using specialized computational pathology workflows and machine learning models.

ChEMBL Database Explorer

Queries the ChEMBL database to retrieve bioactive molecule data, drug targets, and bioactivity measurements for medicinal chemistry research.

Machine Learning Model Evaluation Suite

Analyzes and benchmarks machine learning models using a comprehensive suite of performance metrics and validation tools.

Agilab Streamlit Pages

Enforces robust Streamlit authoring patterns for session state management, widget key hygiene, and high-performance UI development within the AGILAB framework.

USPTO Database & IP Analysis

Interfaces with United States Patent and Trademark Office (USPTO) APIs to perform advanced patent searches, trademark tracking, and intellectual property analysis.

ESM Protein Modeling

Enables advanced protein sequence generation, structure prediction, and representation learning using Evolutionary Scale Modeling.

Polars Data Processing

Performs high-performance data manipulation and analysis using the lightning-fast Polars DataFrame library and Apache Arrow.

PyOpenMS Mass Spectrometry

Analyzes mass spectrometry data for proteomics and metabolomics using the PyOpenMS library.

LaminDB Data Framework

Manages biological data and workflows with integrated lineage tracking, ontology validation, and FAIR compliance.

Pydicom Medical Imaging

Processes and manipulates DICOM medical imaging data for analysis, anonymization, and format conversion.

KEGG Database Connector

Accesses the Kyoto Encyclopedia of Genes and Genomes (KEGG) REST API for biological pathway analysis and molecular interaction networks.

PennyLane Quantum Computing

Builds, trains, and optimizes quantum circuits with hardware-agnostic execution and deep integration with popular machine learning frameworks.

Cirq Quantum Computing

Builds, simulates, and optimizes quantum circuits using Google's Cirq framework for quantum algorithms and hardware execution.

Statistical Analysis Toolkit

Performs comprehensive statistical analysis including hypothesis testing, regression modeling, and Bayesian inference with APA-compliant reporting.

Zarr Python Scientific Data

Optimizes large-scale N-dimensional array storage and processing using chunked, compressed data formats for cloud-native scientific workflows.

Hyperparameter Tuner

Optimizes machine learning model configurations using advanced search strategies to maximize predictive performance and accuracy.