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# Using MLflow on Google Colab

**[Medium](https://daily.dev/sources/medium_js)** · 2 min read · 0 upvotes · 0 comments

## Summary

A practical guide to running MLflow on Google Colab, addressing two key challenges: data persistence and network isolation. Data is persisted across sessions using a SQLite database stored on Google Drive. The MLflow UI (port 5000) is exposed publicly via Ngrok with a static domain to avoid host header errors. Step-by-step code snippets cover mounting Google Drive, configuring the MLflow tracking URI, launching the MLflow server as a background process, and connecting Ngrok to access the UI from a public URL.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://medium.com/@amodahegde/using-mlflow-on-google-colab-b7ad59bd7973>

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Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#data-science](https://daily.dev/tags/data-science), [#devtools](https://daily.dev/tags/devtools), [#sqlite](https://daily.dev/tags/sqlite)

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