What orchestration tools does this skill support?

It provides patterns and templates for major orchestration tools including Apache Airflow, Dagster, Kubeflow Pipelines, and Prefect.

Can I use this for real-time machine learning applications?

Yes, it includes architectural guidance for both batch training pipelines and real-time feature engineering workflows integrated with streaming data.

Does it include model performance monitoring?

Absolutely, the skill covers post-deployment monitoring for model drift, performance regression, and infrastructure latency to ensure production stability.

How does it handle data versioning and reproducibility?

The skill implements best practices for data lineage and versioning using tools like DVC, ensuring every model can be traced back to the exact dataset version used for training.

MLOps Pipeline Workflow

Name: MLOps Pipeline Workflow
Author: HermeticOrmus

byHermeticOrmus

0•

Ciencia de Datos y ML

Orchestrates end-to-end machine learning pipelines from data preparation and training to production deployment and monitoring.

This skill provides a comprehensive framework for building and managing production-ready machine learning lifecycles. It guides users through creating modular, versioned, and observable pipelines using industry-standard orchestration tools like Airflow, Kubeflow, or Dagster. Whether you are automating reproducible training workflows, implementing data validation checks, or setting up canary deployments, this skill ensures best practices for data lineage, experiment tracking, and model serving are integrated into your ML infrastructure for maximum reliability.

Características Principales

01End-to-end DAG orchestration design for Airflow, Kubeflow, and Dagster

02Model training orchestration with integrated experiment tracking

03Automated data validation and feature engineering pipeline templates

04Pre-deployment validation frameworks for performance and regression checks

050 GitHub stars

06Advanced deployment automation including canary and blue-green strategies

Casos de Uso

01Automating continuous training workflows triggered by data drift detection

02Building reproducible batch training pipelines for enterprise ML models

03Implementing modular data processing pipelines with built-in quality checks

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add hermeticormus/hermetic-academy ml-pipeline-workflow

For use in Claude.ai and ChatGPT

Download Skill