MLflow · MLOps

Tracks ML experiments, versions models in the MLflow registry and covers deployment and reproducibility, with autologging for common frameworks.

Orchestra-Research/AI-Research-SKILLs

Designs ML pipeline infrastructure: experiment tracking with MLflow or Weights & Biases, Kubeflow and Airflow orchestration, Feast feature stores and model validation gates.

Jeffallan/claude-skills

ML engineering skill for productionizing models, building MLOps pipelines, and integrating LLMs.

alirezarezvani/claude-skills

Copy skore reports between local, Hub, and MLflow with skore sync, and optionally switch the recorded upload destination.

probabl-ai/skills

Data pipelines, feature stores, and embedding generation for AI/ML systems.

ancoleman/ai-design-components

Build comprehensive ML pipelines, experiment tracking, and model registries with MLflow, Kubeflow, and modern MLOps tools.

aiskillstore/marketplace

Strategic guidance for operationalizing machine learning models from experimentation to production.

ancoleman/ai-design-components

Train ML models on Databricks. An agent skill from databricks/databricks-agent-skills.

databricks/databricks-agent-skills

Selects, deploys, and customizes AI models on Amazon SageMaker.

aws/agent-toolkit-for-aws

MLOps across model deployment, ML pipelines, monitoring, and feature stores.

borghei/Claude-Skills

Guided workflow for taking any ML codebase — including one with no experiment tracking at all, or one full of MLflow 2-era idioms — to a production-grade open-source MLflow 3 setup with…

pproenca/dot-skills

Guide for experiment tracking tool setup (MLflow, Weights & Biases, etc.), reproducibility assurance, model registry, and experiment comparison methodology.

revfactory/harness-100

Automate ML workflows with Airflow, Kubeflow, MLflow. An agent skill from secondsky/claude-skills.

secondsky/claude-skills