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MLOps: Methods and Tools of DevOps for Machine Learning

Altexsoft

When speaking of machine learning, we typically discuss data preparation or model building. Living in the shadow, this stage, according to the recent study , eats up 25 percent of data scientists time. MLOps lies at the confluence of ML, data engineering, and DevOps. More time for development of new models.

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Predibase exits stealth with a low-code platform for building AI models

TechCrunch

“The major challenges we see today in the industry are that machine learning projects tend to have elongated time-to-value and very low access across an organization. “Given these challenges, organizations today need to choose between two flawed approaches when it comes to developing machine learning. .

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Remember when developers reigned supreme? The market for software coding goes soft

CIO

Job titles like data engineer, machine learning engineer, and AI product manager have supplanted traditional software developers near the top of the heap as companies rush to adopt AI and cybersecurity professionals remain in high demand.

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What does an AI consultant actually do?

CIO

The spectrum is broad, ranging from process automation using machine learning models to setting up chatbots and performing complex analyses using deep learning methods. Whether healthcare, retail or financial services each industry presents its own challenges that require specific expertise and customized AI solutions.

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Predictive analytics helps Fresenius anticipate dialysis complications

CIO

German healthcare company Fresenius Medical Care, which specializes in providing kidney dialysis services, is using a combination of near real-time IoT data and clinical data to predict one of the most common complications of the procedure. CIO 100, Digital Transformation, Healthcare Industry, Predictive Analytics

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Turing nabs $32M more for an AI-based platform to source and manage engineers remotely

TechCrunch

” It currently has a database of some 180,000 engineers covering around 100 or so engineering skills, including React, Node, Python, Agular, Swift, Android, Java, Rails, Golang, PHP, Vue, DevOps, machine learning, data engineering and more. Remote work = immediate opportunity.

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10 most in-demand generative AI skills

CIO

Most relevant roles for making use of NLP include data scientist , machine learning engineer, software engineer, data analyst , and software developer. AI image processing enables organizations to analyze and extract data from documents such as invoices, purchase orders, packing lists, receipts, and more.