DataHour: ML oops to MLOps!
DataHour: ML oops to MLOps!
08 Aug 202212:08pm - 08 Aug 202213:08pm
DataHour: ML oops to MLOps!
About the Event
AI is no longer exclusively for digital native companies like Amazon, Netflix, or Uber. Unsurprisingly, Gartner predicts that more than 75% of organizations will shift from piloting AI technologies to operationalizing them by the end of 2024 — which is where the real challenges begin. Unfortunately, scaling AI in this sense isn’t easy. There is a chasm between ML and MLOps that can be tricky to scale, and MLOps can turn into ML-Oops. Getting one or two AI models into production is different from running an entire enterprise or product on AI. And as AI is scaled, problems can (and often do) scale, too.
Organisations that are serious about AI have to adopt a new discipline, “MLOps” or Machine Learning Operations. MLOps is the bridge. It is an engineering culture and practice that aims to unify ML system development and operations to facilitate data processing, ML pipeline, model training, experimentation, evaluation, registry, deployment, monitoring, and serving and scaling. In this webinar you will learn the building blocks of MLOps and the best practices and tools to facilitate rapid, safe, and efficient development and operationalisation of AI.
In this DataHour, Prem Naraindas is going to help you go from ML oops to MLOps
Prerequisites: Enthusiasm for learning Data Science.
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
Who is this DataHour for?
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
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