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Lifecycle of a machine learning project

Episode #359, published Sun, Apr 3, 2022, recorded Tue, Mar 22, 2022.

This episode is carbon neutral.
Are you working on or considering a machine learning project? On this episode, we'll meet three people from the MLOps community: Demetrios Brinkmann, Kate Kuznecova, and Vishnu Rachakonda. They are here to tell us about the lifecycle of a machine learning project. We'll talk about getting started with prototypes and choosing frameworks, the development process, and finally moving into deployment and production.



Links from the show

Demetrios Brinkmann: @DPBrinkm
Kate Kuznecova: linkedin.com
Vishnu Rachakonda: linkedin.com

MLOps Community: mlops.community
Feature stores: mlops.community
Great Expectations: github.com
source control: DVC: dvc.org
StreamLit: streamlit.io
MLOps Jobs: mlops.pallet.com
Made With ML Apps: madewithml.com
Banana.dev: banana.dev
FastAPI: fastapi.tiangolo.com
MLOps without too much Ops: towardsdatascience.com
NBDev: nbdev.fast.ai
The "Works on My Machine" Certification Program: codinghorror.com
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

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