Data Science & ML Claudeスキル

Bayesian Network Fitting and Modification

16

Streamlines Bayesian Network workflows by guiding structure learning, parameter estimation, causal interventions, and network sampling using industry-standard libraries.

PathML

16

Analyzes whole-slide pathology images and multiparametric imaging data using computational tools for tissue segmentation, spatial graphs, and machine learning.

Count Dataset Tokens

16

Calculates token counts in large-scale datasets using specific tokenizers and precise filtering criteria.

MCMC Sampling with Stan

16

Implements Bayesian statistical models and runs MCMC sampling using Stan with comprehensive diagnostic validation.

Caffe Framework & CIFAR-10 Training

16

Guides the compilation of the legacy Caffe deep learning framework and the training of convolutional neural networks on the CIFAR-10 dataset.

Multi-Source Data Merger

16

Merges heterogeneous data sources into unified datasets with automated field mapping and priority-based conflict resolution.

BioServices Bioinformatics Toolkit

16

Provides programmatic access to over 40 bioinformatics web services for biological data retrieval, identifier mapping, and pathway analysis.

PyTorch Model CLI

16

Converts PyTorch neural networks into standalone C/C++ command-line tools by extracting weights and reimplementing inference without Python dependencies.

Caffe CIFAR-10 Build and Training

16

Guides the compilation of the Caffe deep learning framework from source and the execution of CIFAR-10 image classification training workflows.

Small Matrix Eigenvalue Computation

16

Optimizes dominant eigenvalue calculations for small dense matrices by reducing Python wrapper overhead through direct LAPACK integration.

PyTorch Lightning

16

Organizes and scales PyTorch deep learning workflows by automating training loops, hardware orchestration, and boilerplate code.

Distribution Search

16

Optimizes probability distributions to satisfy complex statistical constraints like KL divergence, entropy, and moment conditions through systematic mathematical analysis and numerical search.

Train FastText

16

Optimizes FastText text classification models by balancing hyperparameter tuning with strict file size and accuracy constraints.

GWAS Catalog Explorer

16

Queries the NHGRI-EBI GWAS Catalog for genetic variants, SNP-trait associations, and summary statistics to support genetic epidemiology research.

MTEB Text Retrieval

16

Executes text embedding retrieval and semantic ranking tasks using sentence transformers and cosine similarity metrics.

Exploratory Data Analysis Toolkit

16

Automates comprehensive statistical analysis and visual profiling for diverse datasets to uncover hidden patterns, anomalies, and actionable insights.

CZ CELLxGENE Census

16

Facilitates programmatic access and analysis of the CZ CELLxGENE Census database containing over 61 million single-cell genomics records.

Histolab Digital Pathology

16

Processes whole slide images (WSI) for digital pathology by automating tissue detection, tile extraction, and preprocessing for computational pipelines.

ToolUniverse

16

Integrates over 600 scientific tools and databases for bioinformatics, drug discovery, and computational research into AI-driven workflows.

MuJoCo MJCF Model Tuning

16

Optimizes MuJoCo MJCF model files for simulation performance while maintaining numerical accuracy and physical correctness.

Biomni

16

Executes autonomous multi-step biomedical research tasks including genomics analysis, drug discovery, and clinical interpretation.

DrugBank Database

16

Accesses and analyzes comprehensive pharmaceutical data from DrugBank to perform drug discovery research, interaction analysis, and target identification.

Portfolio Optimization with C Extensions

16

Accelerates Python numerical computations by implementing performance-critical mathematical algorithms as high-speed C extensions.

Data Commons Client

16

Accesses global statistical data from the Data Commons knowledge graph to analyze demographics, economics, health, and environmental trends.

scvi-tools

16

Empowers single-cell omics analysis with deep generative models for dimensionality reduction, batch correction, and multimodal data integration.

Scientific Resource Detection & Strategy

16

Identifies system hardware capabilities and provides data-driven recommendations for optimizing computationally intensive tasks like model training and large-scale data processing.

SHAP Model Interpretability

16

Explains machine learning model predictions and feature importance using Shapley values to provide transparent and actionable AI insights.

AlphaFold Database Access

16

Facilitates the retrieval and analysis of over 200 million AI-predicted protein structures from the AlphaFold DB for biological research and drug discovery.

Modernize Scientific Stack

16

Migrates legacy Python 2 scientific computing code to Python 3 using modern libraries like pandas, numpy, and pathlib.

NeuroKit2 Biosignal Processing

16

Processes and analyzes physiological signals including ECG, EEG, EDA, and respiratory patterns for research and clinical applications.