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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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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.

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Integrating Key Vault Secrets with Azure Synapse Analytics

Apiumhub

Azure Synapse Analytics acts as a data warehouse using dedicated SQL pools, but it is also a comprehensive analytics platform designed to handle a wide range of data processing and analytics tasks on structured and unstructured data. Also combines data integration with machine learning. finance, healthcare).

Azure 89
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What is a data architect? Skills, salaries, and how to become a data framework master

CIO

Information/data governance architect: These individuals establish and enforce data governance policies and procedures. Analytics/data science architect: These data architects design and implement data architecture supporting advanced analytics and data science applications, including machine learning and artificial intelligence.

Data 199