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Continuous Intelligence - Keeping Your AI Application in Production

NDC Conferences via YouTube

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Overview

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This talk explains how to adapt continuous delivery practices to machine learning workflows and keep AI applications in production as code, models, and data change. It discusses pipeline challenges and demonstrates a continuous delivery pipeline with an example application.

Syllabus

Introduction
About Thoughtworks
Open Knowledge
Continuous Delivery for ML
Autoscout
Problems
Continuous Delivery
Pipelines
Challenges
Emily Gorcenski
Code Changes
Model Changes
Data Versioning
Sampling
Schema Changes
Building Pipelines
Developers vs Data Scientists
Continuous Intelligence Pipelines
Continuous Delivery Workflow
Tools and Technologies
Demo
Example Application
Continuous Delivery Pipeline
Conclusion

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NDC Conferences

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