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What is Machine Learning Engineer: Responsibilities, Skills, and Value Brought

Altexsoft

In a world fueled by disruptive technologies, no wonder businesses heavily rely on machine learning. Google, in turn, uses the Google Neural Machine Translation (GNMT) system, powered by ML, reducing error rates by up to 60 percent. The role of a machine learning engineer in the data science team.

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Unlocking the Power of AI with a Real-Time Data Strategy

CIO

By George Trujillo, Principal Data Strategist, DataStax Increased operational efficiencies at airports. Investments in artificial intelligence are helping businesses to reduce costs, better serve customers, and gain competitive advantage in rapidly evolving markets. Instant reactions to fraudulent activities at banks.

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Generative AI will be the key to achieving patient-centric care

CIO

Both healthcare payers and providers remain cautious about how to use this latest version of artificial intelligence, and rightfully so. You have to balance the potential benefits of generative AI with significant, important operational issues, such as ensuring patient data privacy and complying with regulatory requirements.

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Managing Machine Learning Workloads Using Kubeflow on AWS with D2iQ Kaptain

d2iq

Security: Data privacy and security are often afterthoughts during the process of model creation but are critical in production. D2iQ is an AWS Containers Competency Partner , and D2iQ Kaptain is an enterprise Kubeflow product that enables organizations to develop and deploy machine learning workloads at scale.

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AI startup Faculty wins contract to predict future requirements for the UK’s NHS

TechCrunch

Faculty , a VC-backed artificial intelligence startup, has won a tender to work with the NHS to make better predictions about its future requirements for patients, based on data drawn from how it handled the COVID-19 pandemic. We are, I believe, a really effective and scalable AI company, not just for the U.K.

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Smart Factories: Artificial Intelligence and Automation for Reduced OPEX in Manufacturing

DataRobot

This “revolution” stems from breakthrough advancements in artificial intelligence, robotics, and the Internet of Things (IoT). This type of growth has stressed legacy data management systems and makes it nearly impossible to implement a profitable data-centered solution. Factory Monitoring?—?

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AI Chihuahua! Part I: Why Machine Learning is Dogged by Failure and Delays

d2iq

Going from a prototype to production is perilous when it comes to machine learning: most initiatives fail , and for the few models that are ever deployed, it takes many months to do so. As little as 5% of the code of production machine learning systems is the model itself. Adapted from Sculley et al.