MLOps

62 posts in MLOps

Managing and Deploying Multiple Model Versions with Jozu and KitOps: A Smarter Way to Scale ML Workflows

Learn how to manage and deploy multiple ML model versions using Jozu and KitOps. This step-by-step tutorial shows you how to package YOLOv5 models as versioned ModelKits, push them to registries, and deploy on Kubernetes with simple YAML configs. Perfect for teams scaling ML workflows.

MLOps - 12 min read

Build Bulletproof ML Pipelines with Automated Model Versioning

Reproducibility is a major blocker in ML workflows. This tutorial shows how to fix it with version-controlled model packaging and automated rollbacks.

KitOps - 10 min read

Streamlining ML Workflows: Integrating KitOps and Amazon SageMaker

A practical guide to combining model packaging and cloud-based ML tools for efficient machine learning operations.

KitOps - 6 min read

Migrating From DVC to KitOps

A technical comparison of DVC and KitOps, with implementation steps for transitioning ML projects to a containerized workflow.

devops - 6 min read

Jozu Hub–Your private, on-prem Hugging Face registry

A practical guide to managing Hugging Face models with KitOps and Jozu Hub for improved workflow security and deployment.

machinelearning - 1 min read

Maintaining ML Model Accuracy With Automated Drift Detection

DZone published a comprehensive tutorial on detecting and managing data drift in ML systems using KitOps, highlighting automated model retraining to ensure ML models stay accurate in production.