We Build a ML Pipeline After We Deploy

We Build a ML Pipeline After We Deploy

EuroPython Conference via YouTube Direct link

Introduction

1 of 21

1 of 21

Introduction

Class Central Classrooms beta

YouTube videos curated by Class Central.

Classroom Contents

We Build a ML Pipeline After We Deploy

Automatically move to the next video in the Classroom when playback concludes

  1. 1 Introduction
  2. 2 One stop solution
  3. 3 Agenda
  4. 4 Who am I
  5. 5 What is ML pipeline
  6. 6 Why do we need this pipeline
  7. 7 Why automate it
  8. 8 Reduce the cost of any project
  9. 9 When should we use it
  10. 10 When to scale
  11. 11 Building blocks
  12. 12 Continuous Integration
  13. 13 Continuous Delivery
  14. 14 Automated Pipeline
  15. 15 Continuous Delivery Process
  16. 16 Monitoring
  17. 17 Engineering
  18. 18 Debugging
  19. 19 Top 3 debugging issues
  20. 20 Python libraries
  21. 21 QA time

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.