Xebia
FEBRUARY 29, 2024
Introduction Azure Machine Learning (Azure ML) is a popular machine learning service. Azure ML provides a lot of predefined functionality for deploying machine learning model endpoints, which is great. Use the Azure ML Python SDK to configure and manage deployment to Azure ML.
CIO
JANUARY 19, 2024
The exam covers everything from fundamental to advanced data science concepts such as big data best practices, business strategies for data, building cross-organizational support, machine learning, natural language processing, scholastic modeling, and more. It’s a fundamentals exam, so you don’t need extensive experience to pass.
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CIO
APRIL 9, 2024
Previously head of cybersecurity at Ingersoll-Rand, Melby started developing neural networks and machine learning models more than a decade ago. We just came out of the gates fast, and we just kept solving problems,” the CIO says, noting that his team was experimenting with Azure LLMs before they were on the market. “We
InfoWorld
MARCH 21, 2024
With KubeCon Europe taking place this week, Microsoft has delivered a flurry of Azure Kubernetes announcements.
Palo Alto Networks
MAY 2, 2023
That’s why we are excited to launch Cloud NGFW for Azure to strengthen security for applications running on Microsoft Azure while streamlining network security operations. The added strength of Panorama integration makes Cloud NGFW for Azure even more powerful. No need to learn new tools or create new processes.
Mentormate
MAY 31, 2023
In this article, we will discuss how MentorMate and our partner eLumen leveraged natural language processing (NLP) and machine learning (ML) for data-driven decision-making to tame the curriculum beast in higher education. Here, we will primarily focus on drawing insights from structured and unstructured (text) data.
Altexsoft
JULY 23, 2020
When speaking of machine learning, we typically discuss data preparation or model building. The fusion of terms “machine learning” and “operations”, MLOps is a set of methods to automate the lifecycle of machine learning algorithms in production — from initial model training to deployment to retraining against new data.
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