CIO Business Intelligence
FEBRUARY 22, 2024
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.
Corinium
JUNE 6, 2019
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 is the most common mistake people make around data?
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Rocket-Powered Data Science
JULY 6, 2021
2) MLOps became the expected norm in machine learning and data science projects. MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase. 5) The emergence of Edge-to-Cloud architectures clearly began pushing Industry 4.0
DataKitchen
APRIL 13, 2021
Metis Machine — Enterprise-scale Machine Learning and Deep Learning deployment and automation platform for rapid deployment of models into existing infrastructure and applications. Polyaxon — An open-source platform for reproducible machine learning at scale. Kubeflow — The Machine Learning Toolkit for Kubernetes.
O'Reilly on Data
SEPTEMBER 11, 2019
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.
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