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Benefits of the Cloud: IT vs. Data Science

Open Data Group October 30, 2018
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Deploying machine learning models is often a bottle neck in realizing the value from data science investments. Utilizing the cloud, combined with a microservices based infrastructure, to deploy machine learning models can make the process less complex, and make life easier for everyone involved. Let’s look into how analytic migration to the cloud can help the data science and IT teams specifically:

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Analytic Deployment Stacks and Frameworks (Part 1): Motivation

Garrett Long February 9, 2017
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This is part 1 in a multi-part series discussing an approach to effective deployment of analytic models at scale.  

It’s 2017. Your organization has been collecting valuable data for several years.  The organization you work for is somewhere on the spectrum of analytic maturity from “we just hired our first data scientist” to “we are in the credit scoring business and have been developing critical analytics for decades”.

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7/20 Meet-Up: Model Deployment with Bob Grossman

Garrett Long July 26, 2016
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Last Wednesday, Open Data Group had the opportunity to co-host a data science meet-up with DataScope, which manages the Data Science Chicago Meet-Up. We thoroughly enjoyed the experience and appreciate all the folks who came out for discussion and pizza. Bob Grossman, Open Data’s founder and Chief Data Scientist, introduced the concept of AnalyticOps (read CTO Stu Bailey’s posts on the same topic here) and the emerging core competency of deploying models. Bob was joined by Robert Nendorf from Allstate, who shared his views on a similar topic: DevOps for Data Science.

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AnalyticOps: Part 4 - What is AnalyticOps?

Garrett Long June 8, 2016
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How is AnalyticOps different than DevOps or Data Science?

Well, it took four parts to get to this point, but we’ve used our time to discuss some of the abstractions that are required to understand the idea referred to as “AnalyticOps”. Our journey started with the abstract concept of “what is an analytic” while the second covered the operative concept of “deploying” the analytic with an analytic engine or deployment server.  

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