Remove 2019 Remove Deep Learning Remove Experimentation Remove IoT
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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

In the long run, we see a steep increase in the proliferation of all types of data due to IoT which will pose both challenges and opportunities. It is also important to have a strong test and learn culture to encourage rapid experimentation. What are you most looking forward to about CDAOI Insurance 2019?

Insurance 250
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The DataOps Vendor Landscape, 2021

DataKitchen

ParallelM — Moves machine learning into production, automates orchestration, and manages the ML pipeline. Acquired by DataRobot June 2019). Metis Machine — Enterprise-scale Machine Learning and Deep Learning deployment and automation platform for rapid deployment of models into existing infrastructure and applications.

Testing 307
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Topics to watch at the Strata Data Conference in New York 2019

O'Reilly on Data

Our call for speakers for Strata NY 2019 solicited contributions on the themes of data science and ML; data engineering and architecture; streaming and the Internet of Things (IoT); business analytics and data visualization; and automation, security, and data privacy. Deep learning,” for example, fell year over year to No.

IoT 20