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Git-Based CI-CD for ML

Open Data Science via YouTube

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Overview

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This session explains how to use Git-based pipelines to bring machine learning into production, including automated training, model review, versioned artifacts, deployment, monitoring, and collaboration. It includes a live demonstration using open-source MLOps tools and hosted training and serving environments.

Syllabus

Introduction
The problem
The siloed approach
The production approach
What do we need to do
Problem 1 Silos
Operational Pipeline
Transformation
Serverless
Four Big Pillars
Feature Store
Operations Store
Realtime Pipeline
CICD Automation
ML Project
Pipeline Exports
ML Run
Training
Demo
Deploy serving function
Build topology
Mock server
Pipeline notebook
Pipeline workflow

Taught by

Open Data Science

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