Lifecycle of a machine learning project
Episode #359,
published Sun, Apr 3, 2022, recorded Tue, Mar 22, 2022
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
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
--- Stay in touch with us ---
Subscribe to us on YouTube: youtube.com
Follow Talk Python on Mastodon: talkpython
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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
--- Stay in touch with us ---
Subscribe to us on YouTube: youtube.com
Follow Talk Python on Mastodon: talkpython
Follow Michael on Mastodon: mkennedy