Remove Deep Learning Remove Experimentation Remove IoT Remove Visualization
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Ferrovial puts AI at the heart of its transformation

CIO Business Intelligence

With the aim to accelerate innovation and transform its digital infrastructures and services, Ferrovial created its Digital Hub to serve as a meeting point where research and experimentation with digital strategies could, for example, provide new sources of income and improve company operations.

IT 105
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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 advances do you see in Visual Analytics in the next five years?

Insurance 250
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The DataOps Vendor Landscape, 2021

DataKitchen

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. Polyaxon — An open-source platform for reproducible machine learning at scale. Kubeflow — The Machine Learning Toolkit for Kubernetes. Meta-Orchestration .

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