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Classroom Contents
CI-CD for Machine Learning
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- 1 Introduction
- 2 Agenda
- 3 Common Problems
- 4 Assumptions
- 5 What is CML
- 6 Getting started with CML
- 7 Example report
- 8 CML Runner
- 9 TwoStep Workflow
- 10 Do we need reports
- 11 CICD workflow
- 12 Live demo
- 13 Training script
- 14 CI configuration
- 15 Change hyper parameters
- 16 Commit changes
- 17 Neural style transfer
- 18 CI script
- 19 Change style image
- 20 Pipelines
- 21 GPU
- 22 QA
- 23 Automation
- 24 Is automation important
- 25 Can we follow standard practices without CML
- 26 How do you configure AWS resources
- 27 What if I submit multiple changes near each other
- 28 Streaming data
- 29 Running notebooks
- 30 CloudSpot
- 31 Installing CML
- 32 CML vs ML Flow
- 33 Docker Image
- 34 Mobile ML
- 35 DVC vs ML Flow
- 36 Preventing Emergence
- 37 CML vs Terraform
