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Monitoring your ML pipelines
About This Webinar
Once your machine learning models are in production you are not done, you are just getting started. The model will have to face its worst enemy: The Real World!
We'll look into what kinds of monitoring you can put in place in order to understand how your model is performing. This considers both, continuous training as well as the usage of the trained model. It looks into:
Monitoring your infrastructure
Monitoring the data
Monitoring the training
Monitoring value in the real world
Who can view: People who attended or registered for the webinar only
Webinar Price: Free
Featured Presenters
Senior Data Scientist
Kristina is a senior data scientist at BCG Digital Ventures, where she works on projects spanning a variety of industries.
She completed her MSc, which focused on temporal data clustering using evolutionary computation, at the University of Pretoria in South Africa. During and after her research she worked as a software engineer at the SAP innovation centre, Entelect (a consulting firm) and moved back into data engineering and data science through her work at Soundcloud and BCG Digital Ventures.
Her world does not just consist of data and engineering, but stretches into the humanities through her passion for computational archaeology, creative writing and painting.
She completed her MSc, which focused on temporal data clustering using evolutionary computation, at the University of Pretoria in South Africa. During and after her research she worked as a software engineer at the SAP innovation centre, Entelect (a consulting firm) and moved back into data engineering and data science through her work at Soundcloud and BCG Digital Ventures.
Her world does not just consist of data and engineering, but stretches into the humanities through her passion for computational archaeology, creative writing and painting.
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