Comprehensive MLOps workflows for the complete ML lifecycle - experiment tracking, model registry, deployment patterns, monitoring, A/B testing, and production best practices with MLflow
Comprehensive MLOps workflows for the complete ML lifecycle - experiment tracking, model registry, deployment patterns, monitoring, A/B testing, and production best practices with MLflow
Category: developer (开发工具) · Author: manutej · Version: @main
Tags: mlops, mlflow, experiment-tracking, model-registry, deployment, monitoring, ml-lifecycle, feature-stores, ci-cd, model-versioning, a-b-testing, production-ml
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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, deployment, monitoring, ml-lifecycle, feature-stores, ci-cd, model-versioning, a-b-testing, production-ml