web02.fireside.fm Wed, 22 Apr 2026 08:48:53 -0500 Fireside (https://fireside.fm) Pipeline Conversations - Episodes Tagged with “Aws” https://podcast.zenml.io/tags/aws Thu, 16 Dec 2021 16:30:00 +0100 Pipeline Conversations brings you interviews with platform engineers, ML practitioners, and technical leaders building production AI systems. We dig into the real challenges of MLOps and LLMOps: orchestrating complex workflows on Kubernetes, fine-tuning and evaluating models at scale, and shipping AI that actually works. From ZenML. en-us episodic MLOps and LLMOps, from the trenches ZenML GmbH Pipeline Conversations brings you interviews with platform engineers, ML practitioners, and technical leaders building production AI systems. We dig into the real challenges of MLOps and LLMOps: orchestrating complex workflows on Kubernetes, fine-tuning and evaluating models at scale, and shipping AI that actually works. From ZenML. no machine-learning, machinelearning, mlops, deeplearning, ai, artificialintelligence, artificial-intelligence, technology, tech, mlops, llmops ZenML GmbH podcast@zenml.io Monitoring Your Way to ML Production Nirvana with Danny Leybzon https://podcast.zenml.io/ml-monitoring-danny-leybzon d5f677ea-92d0-421a-85e2-918f549ec265 Thu, 16 Dec 2021 16:30:00 +0100 ZenML GmbH full ZenML GmbH 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. 40:34 no 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. As such, we had a really interesting discussion of some of the ways that tooling and the general context for data science sometimes lets practitioners down, And of course we also discussed why monitoring and logging is actually a kind of baseline practice that should be part of any and every data scientist's toolkit. Luckily for us, Danny added in a bunch of examples from his wide experience doing all this in the real world. Special Guest: Danny Leybzon. mlops, aws, machine-learning, zenml, industry 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.

As such, we had a really interesting discussion of some of the ways that tooling and the general context for data science sometimes lets practitioners down,
And of course we also discussed why monitoring and logging is actually a kind of baseline practice that should be part of any and every data scientist's toolkit. Luckily for us, Danny added in a bunch of examples from his wide experience doing all this in the real world.

Special Guest: Danny Leybzon.

Links:

]]> 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.

As such, we had a really interesting discussion of some of the ways that tooling and the general context for data science sometimes lets practitioners down,
And of course we also discussed why monitoring and logging is actually a kind of baseline practice that should be part of any and every data scientist's toolkit. Luckily for us, Danny added in a bunch of examples from his wide experience doing all this in the real world.

Special Guest: Danny Leybzon.

Links:

]]> Practical MLOps with Noah Gift https://podcast.zenml.io/practical-mlops-noah-gift ca401b71-399e-4ce5-9497-f155b2be108b Thu, 02 Dec 2021 09:45:00 +0100 ZenML GmbH full ZenML GmbH 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. 47:14 no 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. Read the summary blogpost (https://blog.zenml.io/practical-mlops-noah-gift/) on the ZenML blog. Special Guest: Noah Gift. mlops, aws, automl, machine-learning, deep-learning, zenml 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.

Read the summary blogpost on the ZenML blog.

Special Guest: Noah Gift.

Links:

]]> 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.

Read the summary blogpost on the ZenML blog.

Special Guest: Noah Gift.

Links:

]]>