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Machine Learning Operations (MLOps or ML Ops) is a set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently, as defined in various publications. In this podcast we take on the topic of MLOPs. What is it and is it like DevOps for AI? Turns out it’s broader than you might think including everything monitoring to governance and explainability. Adewumni shares why it's both necessary and exciting.
For her 30 second recommendation, Ade shared the Cloudera Fast Forward Labs blog which can be found here. She also mentioned a report by the Algorithmic Justice League on bug bounties for algorithmic harms which can be found here.
You can follow Ade on Twitter @Adewunmi and @FastForwardLabs . You can also find her on Medium medium.com/@adeadewunmi and LinkedIn here.
You can follow me on Twitter @MaribelLopez and on LinkedIn here.
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Machine Learning Operations (MLOps or ML Ops) is a set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently, as defined in various publications. In this podcast we take on the topic of MLOPs. What is it and is it like DevOps for AI? Turns out it’s broader than you might think including everything monitoring to governance and explainability. Adewumni shares why it's both necessary and exciting.
For her 30 second recommendation, Ade shared the Cloudera Fast Forward Labs blog which can be found here. She also mentioned a report by the Algorithmic Justice League on bug bounties for algorithmic harms which can be found here.
You can follow Ade on Twitter @Adewunmi and @FastForwardLabs . You can also find her on Medium medium.com/@adeadewunmi and LinkedIn here.
You can follow me on Twitter @MaribelLopez and on LinkedIn here.