The MLOps Podcast
A podcast by Dean Pleban @ DagsHub
34 Episodes
-
π΄π’π£Julia Language in Production with Logan Kilpatrick
Published: 21/11/2022 -
π Building tools for MLOps with Guy Smoilovsky
Published: 18/10/2022 -
π You Have Too Much Data with Dean Langsam
Published: 16/09/2022 -
π Reasonable Scale MLOps with Jacopo Tagliabue
Published: 22/08/2022 -
π¦Ύ Made With ML - Learning How to Apply MLOps with Goku Mohandas
Published: 18/07/2022 -
π€ΉββοΈ Building models that actually perform with Kyle Gallatin
Published: 20/06/2022 -
π¬ MLOps for NLP Systems with Charlene Chambliss
Published: 16/05/2022 -
π§© Simplifying Complex Ideas with Yannic Kilcher
Published: 18/04/2022 -
π₯ Getting Data Scientists to Write Better Code with Laszlo Sragner
Published: 14/02/2022 -
π MLOps lessons learned helping companies build their ML systems with Lee Harper, Lead DS at Catapult
Published: 04/11/2021 -
π§ Algorithmic challenges in bringing ML models into production with Roey Mechrez, CTO at BeyondMinds
Published: 20/09/2021 -
π€ Feature stores and CI/CD for machine learning with Qwak.ai VP Engineering, Ran Romano
Published: 11/08/2021 -
π€ Large ML models in production with HuggingFace CTO Julien Chaumond
Published: 04/07/2021 -
π£ Finding your path in ML with NLP Engineer Urszula Czerwinska
Published: 27/04/2021
A podcast from DagsHub about bringing machine learning into the real world. Each episode features a conversation with top data science and machine learning practitioners, who'll share their thoughts, best practices, and tips for promoting machine learning to production
