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Machine learning model serving architectures

Xebia

After months of crunching data, plotting distributions, and testing out various machine learning algorithms you have finally proven to your stakeholders that your model can deliver business value. For the sake of argumentation, we will assume the machine learning model is periodically trained on a finite set of historical data.

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Swiss energy services company uses machine learning to see the future

CIO

Swiss energy services company IWB has a vision of a world with a fully renewable, climate-friendly energy supply. The new installations shifted the consumption trend, resulting in a higher network load, impacting electric utility company distribution grids. Not long ago, though, that goal seemed difficult to conceptualize.

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Enhancing customer care through deep machine learning at Travelers

CIO

s nest perspective of immediate and long-term tasks to equally strengthen the company culture and customer needs. s unique about the [chief data officer] role is it sits at the cross-section of data, technology, and analytics,â?? s unique about the role is it sits at the cross-section of data, technology, and analytics.

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AWS adds machine learning capabilities to Amazon Connect

CIO

In a bid to help enterprises offer better customer service and experience , Amazon Web Services (AWS) on Tuesday, at its annual re:Invent conference, said that it was adding new machine learning capabilities to its cloud-based contact center service, Amazon Connect.

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5 Things a Data Scientist Can Do to Stay Current

And more is being asked of data scientists as companies look to implement artificial intelligence (AI) and machine learning technologies into key operations. Fostering collaboration between DevOps and machine learning operations (MLOps) teams. Collecting and accessing data from outside sources.

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Hugging Face reaches $2 billion valuation to build the GitHub of machine learning

TechCrunch

Lux Capital is leading the round, with Sequoia and Coatue investing in the company for the first time. When I first covered the company in 2017, the startup was focused on a consumer app. That consumer bet hasn’t paid off, but the company kept iterating on its natural language processing technology.

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Getting Machine Learning Projects from Idea to Execution

Harvard Business Review

Machine learning might be the world’s most important general-purpose technology, but it’s notoriously difficult to launch. Outside of Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What’s missing?

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Data Science Fails: Building AI You Can Trust

The game-changing potential of artificial intelligence (AI) and machine learning is well-documented. Any organization that is considering adopting AI at their organization must first be willing to trust in AI technology.

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Realizing the Benefits of Automated Machine Learning

While everyone is talking about machine learning and artificial intelligence (AI), how are organizations actually using this technology to derive business value? This white paper covers: What’s new in machine learning and AI. Real-world examples of companies using the DataRobot automated machine learning platform.