SlideShare a Scribd company logo
Version Control for
Machine Learning Projects
@mroutis
About me
- Name: Ramón Valles
- Handle: mroutis
- Work: Software developer
- Company: iterative.ai
@mroutis
Iterative AI
Time
&
Effort
@mroutis
(Data Version Control)
Why versioning is important?
@mroutis
Datasets evolve over time
@mroutis
Different models
@mroutis
https://scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html
“Yea, we have version control”
@mroutis
https://www.reddit.com/r/ProgrammerHumor/comments/63rcvc/yea_we_have_version_control/
How do we identify each version?
@mroutis
https://www.reddit.com/r/ProgrammerHumor/comments/99a9k8/version_control
@mroutis
Manual work is error prone.
@mroutis
Is versioning data / models enough?
@mroutis
Reproducibility Crisis
“I was recently chatting to a friend whose startup’s
machine learning models were so disorganized...
training the same model get different results!”
- Peter Warden (2018)
https://petewarden.com/2018/03/19/the-machine-learning-reproducibility-crisis/
@mroutis
@mroutis
What have been done
so far to address this?
@mroutis
@mroutis
Tracking experiments
Manual work is error prone.
@mroutis
@mroutis
Pipelines
- Chain processes together
- Reproduce in the correct order
- Make it easier to return to old work
- The output of one stage is the input of the next on
@mroutis
Pipelines
How does DVC address this problems?
@mroutis
@mroutis
@mroutis
Versioning with DVC
@mroutis
Pipelines with DVC
@mroutis
@mroutis
Experiment Tracking with DVC
@mroutis
Reproduce experiments
@mroutis
Collaborate
Want to learn more?
- Check out docs: https://dvc.org/doc
- Chat with us: https://dvc.org/chat
- Contribute on GitHub: https://github.com/iterative/dvc
- Follow us on Twitter: @DVCorg
@mroutis
Thanks for listening!
@mroutis
Thanks for Listening - Chris Thile
Thanks for the invitation!

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