Operationalizing Data Science: The Right Architecture and Tools

November 6, 2017
In part one of this two-part series, you learned some of the common reasons enterprises struggle to turn insights into actions as well as a strategy for overcoming these challenges to successfully operationalize data science. In part two, it’s time to fill in the architectural and technological details of that strategy. Pivotal Data Scientist Megha Agarwal will share the key ingredients to successfully put data science models in production and use them to drive actions in real-time. In this webinar, you will learn: - Adopting extreme programming practices for data science - Importance of working in a balanced team - How to put and maintain machine learning models in production - End-to-end pipeline design Presenter: Megha Agarwal, Data Scientist
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Not actually a DevOps Talk
Not actually a DevOps Talk

Not actually a DevOps Talk Or, beyond "survival is not mandatory" by Michael Coté November 2017

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