Hamza Tahir
Co-Host of Pipeline Conversations
Hamza Tahir has hosted six Episodes.
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ZenML MLOps Competition
September 26th, 2022 | Season 2 | 8 mins 13 secs
competition, mlops, open-source, zenml
So excited to be able to announce our :fire: AMAZING :fire: external judges for the ZenML Month of MLOps competition! We have a stellar panel of :sparkles: ML and MLOps heroes :sparkles: to help select the best pipelines from all of your submissions!
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ZenML Recap with Adam and Hamza
April 28th, 2022 | 25 mins 31 secs
mlops, open-source, zenml
Adam and Hamza return for a short discussion of what we've been busy working on during the previous few months, where we're going with ZenML and why it's so amazing to be building an open-source tool.
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Creating Tools that Spark Joy with Ines Montani
January 13th, 2022 | 43 mins 46 secs
data-science, machine-learning, nlp, open-source
Our guest this week is Ines Montani, co-founder and CEO of Explosion, a company based out of Berlin that produce tools that you probably know and love like Spacy, a Python Natural Language Processing library and Prodigy, a data annotation tool.
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Monitoring Your Way to ML Production Nirvana with Danny Leybzon
December 16th, 2021 | 40 mins 34 secs
aws, machine-learning, mlops, zenml
This week, we spoke with Danny Leybzon, currently working with WhyLabs to help data scientists monitor their models in production and prevent model performance from degrading. He previously worked as a kind of roving data scientist and engineer, helping companies put their models into production.
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Practical MLOps with Noah Gift
December 2nd, 2021 | 47 mins 14 secs
aws, machine-learning, mlops
Noah Gift is the founder of Pragmatic A.I. Labs and author of 'Practical MLOps'. We discuss the role of MLOps in an organisation, some deployment war stories from his career as well as what he considers to be 'best practices' in production machine learning.
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Introducing ZenML
November 19th, 2021 | 22 mins 18 secs
mlops, zenml
Adam and Hamza introduce themselves for the first episode of Pipeline Conversations. They discuss the world of MLOps, where ZenML sits within this space, and why it's such a complicated problem to solve.