MLOps Strategy to Advance Machine Learning Apps

DevOps vs. MLOps

3-Step Process for Utilizing DevOps in ML

ML Process Overview

Step 1: Data Preparation

Step 2: Model Training

Model Building, Re-Training, Registry, and Deployment

Step 3: ML Model Deployment

Essential DevOps Practices

Customer Journey in ML Automation

Steps in ML Workflow
  • Code Repository
  • Data Version Control
  • Feature Store (for sharing and discovering curated features)
  • Model artifact versioning (managing model version at scale and establishing traceability)
MLOps Workflow Diagram

MLOps Accelerator

MLOps Accelerator

Wrapping Everything Up



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Neurons Lab

Neurons Lab

We are a group of scientists, engineers, and developers who are passionate to revolutionize the future of businesses with AI and machine learning technologies.