Skills matching the name, description or GitHub author.
Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox mo...
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU...
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparamet...
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparamet...
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU...
Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox mo...
Build production Firebase Genkit applications including RAG systems, multi-step flows, and tool calling for Node.js/Python/Go. Deploy to Firebase Functions or Cloud Run with AI monitoring. Use when asked to "cr...
Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API) or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, HF Space...
Run Python code on cloud GPUs using Modal serverless platform. Use when you need A100/T4/A10G GPU access for training ML models. Covers Modal app setup, GPU selection, data downloading inside functions, and res...
Guidance for converting R-Stan (RStan) code to Python-Stan (PyStan). This skill applies when translating Stan models and inference code from R to Python, including API mapping between RStan and PyStan 3.x, hype...
Guidance for implementing CLI tools that perform inference using PyTorch models in native languages (C/C++/Rust). This skill should be used when tasks involve extracting weights from PyTorch .pth files, impleme...
Guidance for creating standalone CLI tools that perform neural network inference by extracting PyTorch model weights and reimplementing inference in C/C++. This skill applies when tasks involve converting PyTor...
This skill provides guidance for translating RStan (R-based Stan interface) code to PyStan (Python-based Stan interface). It should be used when converting Stan models from R to Python, migrating Bayesian infer...
SAP HANA Machine Learning Python Client (hana-ml) development skill. Use when: Building ML solutions with SAP HANA's in-database machine learning using Python hana-ml library for PAL/APL algorithms, DataFrame...
Data processing, analysis, and visualization with Python/JavaScript. Use for data exploration, pandas operations, chart generation, and insights extraction.
Expert guidance for regression analysis, statistical modeling, and outlier detection in Python using statsmodels, scikit-learn, scipy, and PyOD - includes model diagnostics, assumption checking, robust methods,...
Expert guidance for mathematical optimization in Python - systematic problem classification, library selection (scipy, pyomo, cvxpy, GEKKO), solver configuration, and implementation patterns for LP, QP, NLP, MI...
Expert guidance for multiobjective optimization in Python - Pareto optimality, evolutionary algorithms (NSGA-II, NSGA-III, MOEA/D), scalarization methods, Pareto front analysis, and implementation with pymoo, p...
Google Agent Development Kit (ADK) for Python. Capabilities: AI agent building, multi-agent systems, workflow agents (sequential/parallel/loop), tool integration (Google Search, Code Execution), Vertex AI deplo...
Computational text analysis for sociology research using R or Python. Guides you through topic models, sentiment analysis, classification, and embeddings with systematic validation. Supports both traditional (L...
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparamet...
Build production Firebase Genkit applications including RAG systems, multi-step flows, and tool calling for Node.js/Python/Go. Deploy to Firebase Functions or Cloud Run with AI monitoring. Use when asked to "cr...
Implement AI/ML research papers from scratch when no official code exists. Use when the user wants to reproduce a paper, implement an algorithm from a PDF, build a model architecture from a research paper, or c...
Build AI agents with Google's Agent Development Kit (ADK) Python. Use when building AI agents with tool integration, multi-agent systems, workflow agents (sequential, parallel, loop), or deploying to Vertex AI.
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