Track ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow - framework-agnostic ML lifecycle platform
Track ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow - framework-agnostic ML lifecycle platform
跟踪机器学习实验，管理具有版本控制的模型注册，部署模型到生产环境，并使用 MLflow 重现实验 - 与框架无关的机器学习生命周期平台
Category: developer (开发工具) · Author: davila7 · Version: @main · License: MIT
Tags: MLOps, MLflow, Experiment Tracking, Model Registry, ML Lifecycle, Deployment, Model Versioning, PyTorch, TensorFlow, Scikit-Learn, HuggingFace
该 Skill 暂无文档文件。
Search for places (restaurants, cafes, etc.) via Google Places API proxy on localhost.
Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Start voice calls via the OpenClaw voice-call plugin.
Notion API for creating and managing pages, databases, and blocks.
Gemini CLI for one-shot Q&A, summaries, and generation.
Category:developer
Tags:MLOps, MLflow, Experiment Tracking, Model Registry, ML Lifecycle, Deployment, Model Versioning, PyTorch, TensorFlow, Scikit-Learn, HuggingFace