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MLOps and the evolution of data science

IBM Journey to AI blog

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

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3 Takeaways from Gartner’s 2018 Data and Analytics Summit

DataRobot Blog

Today’s data management and analytics products have infused artificial intelligence (AI) and machine learning (ML) algorithms into their core capabilities. These modern tools will auto-profile the data, detect joins and overlaps, and offer recommendations. 2) Line of business is taking a more active role in data projects.

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Who is a BI Developer: Role, Responsibilities & Skills

Pickl AI

It frequently requires the use of specialised software and tools to aid in the gathering and analysis of data from many different places such as spreadsheets, tables of information, and enterprise systems. billion in 2015 and reached around $26.50 billion in 2021. What Does a BI Developer Do?

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McKinsey QuantumBlack on automating data quality remediation with AI

Snorkel AI

We were ultimately acquired about six-and-a -half years ago now, at the very end of 2015. But a lot of what we’re talking about here is trying to build data pipelines that are going to run. The last few years have been something of a scaling journey. That’s easy and uses contextual-based anomaly approaches.

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McKinsey QuantumBlack on automating data quality remediation with AI

Snorkel AI

We were ultimately acquired about six-and-a -half years ago now, at the very end of 2015. But a lot of what we’re talking about here is trying to build data pipelines that are going to run. The last few years have been something of a scaling journey. That’s easy and uses contextual-based anomaly approaches.

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McKinsey QuantumBlack on automating data quality remediation with AI

Snorkel AI

We were ultimately acquired about six-and-a -half years ago now, at the very end of 2015. But a lot of what we’re talking about here is trying to build data pipelines that are going to run. The last few years have been something of a scaling journey. That’s easy and uses contextual-based anomaly approaches.

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How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Flipboard

Iris was designed to use machine learning (ML) algorithms to predict the next steps in building a data pipeline. His entrepreneurial journey began with his college startup, STAK, which was later acquired by Carvertise with Aaron contributing significantly to their recognition as Tech Startup of the Year 2015 in Delaware.

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