by Iguazio | Jul 25, 2022 | Uncategorized
In this session Yaron Haviv discusses how to enable continuous delivery of machine learning to production using Git based ML pipelines (Github Actions) with hosted training and model serving environments. Yaron touches upon how to leverage Git to solve rigorous MLOps...
by Iguazio | Jun 15, 2022 | Uncategorized
Operationalizing AI pipelines is notoriously complex. For deep learning applications, the challenge is even greater, due to the complexities of the types of data involved. Without a holistic view of the pipeline, operationalization can take months, and will require...
by Iguazio | May 18, 2022 | Uncategorized
The Evolving Meaning of ‘MLOps’ When you say ‘MLOps’, what do you mean? As the technology ecosystem around ML evolves, ‘MLOps’ now seems to have (at least) two very different meanings: One common usage of ‘MLOps’ refers to the cycle of training an AI model: preparing...
by Iguazio | May 4, 2022 | Uncategorized
Iguazio’s Data Scientist discusses how to detect and handle problems that arise when models lose their accuracy and how to implement concept drift detection and remediation in production. He shows how to automate MLOps processes at scale, to handle drift detection...
by Iguazio | Apr 27, 2022 | Uncategorized
David Aronchick, Head of OSS ML Strategy at Microsoft, Marvin Buss, Azure Customer Engineer at Microsoft, and Zander Matheson, Senior Data Scientist at Github discuss using Git to enable continuous delivery of machine learning to production, enable controlled...
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