Speaker: Alex Sadovsky, Sr. Director of Data Science, Oracle Data Cloud
Presentation: Data scientists are expected to wear many hats in an organization. Many tasks often fall in the realm of data science – ingesting and cleaning data, managing data storage, creating scalable machine learning models, and publishing APIs to expose and schedule services for end users. This talk focuses on how to create end-to-end data science products that allow data scientists to focus on business logic, all while embracing nearly infinitely horizontally scalable data platforms. To do this, we’ll explore server-less cloud technologies at multiple levels of the data science pipeline such as server-less compute, workflow, containerized workloads, distributed on-demand machine learning, metrics tracking, and API as a service. At the end of this talk we’ll have a prototype for an end-to-end machine learning system, on a scalable cloud platform, capable of processing petabytes of data and thousands of requests without the need for any freestanding servers.
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