Domain Ml
actionbook/rust-skillsBuilding machine learning applications in Rust requires careful planning. You need to handle large data efficiently and use GPU acceleration for speed. This skill gives you the rules and patterns to do that.
It covers memory efficiency by avoiding copying tensors. It shows how to use GPU batching for better performance. You also learn about standard model formats like ONNX for moving between Python and Rust.
With code examples for inference servers and batched predictions, you can build fast and reliable ML systems. The skill helps you choose the right Rust libraries like candle, burn, or tract for your task.
Add Domain Ml skill to your workflow
Global
mkdir -p ~/.claude/skills/domain-mlProject
mkdir -p .claude/skills/domain-mlSource Repository
More Data Science & ML Claude Code Skills
Env And Assets Bootstraplllllllama/ai-paper-reproduction-skill
Prepare conda-first environment and asset paths for deep learning reproduction
Env And Assets Bootstraplllllllama/rigorpilot-skills
Safe and careful setup of conda environments and asset paths for deep learning reproduction
Run Trainlllllllama/rigorpilot-skills
Run deep learning training conservatively with structured logs and metrics
Explore Runlllllllama/rigorpilot-skills
Plan and rank quick deep learning exploration runs with clear boundaries
Powerbi Modelinggithub/awesome-copilot
Expert guidance for building optimized Power BI semantic models with star schemas and DAX
Power Bi Dax Optimizationgithub/awesome-copilot
Make your Power BI DAX formulas faster and easier to maintain
Power Bi Model Design Reviewgithub/awesome-copilot
Review your Power BI data model design to improve speed and reliability
Power Bi Performance Troubleshootinggithub/awesome-copilot
Find and fix Power BI performance issues with clear step by step guidance