Wednesday, November 20 • 4:25pm - 5:00pm
Realizing End to End Reproducible Machine Learning on Kubernetes - Suneeta Mall, Nearmap

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Industry adaptation of data-science has grown rapidly in the last few years. The probabilistic nature of this space requires the right tools and techniques to ensure that the answers produced are reliable. Models are derived from data, which is almost always evolving, massive (as in deep-learning), and requiring clean-up and pre-processing before use. Reproducibility, reporting, tracking and management around the tasks of 1) data - collection, pre-processing, often feature engineering and 2) model – training, tuning, evaluation and serving are essential.

With tools such as Pachyderm, Kubeflow, Katib, ModelDB, Seldon and Argo, an automated end-to-end reproducible machine learning framework can be built on Kubernetes. This talk will detail how the aforementioned tools can be used to build an automated, reproducible machine learning framework.

avatar for Suneeta Mall

Suneeta Mall

Senior Data Scientist, Nearmap
Suneeta Mall is a Senior Data Scientist at Nearmap. She is leading the engineering efforts of Artificial Intelligence division at Nearmap. In the past, she has led the efforts of migrating Nearmap's engineering framework to Kubernetes. In her 12 years of software industry experience... Read More →

Wednesday November 20, 2019 4:25pm - 5:00pm
Room 16AB - San Diego Convention Center Mezzanine Level