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The rise of machine learning applications in healthcare

Dataconomy

Machine learning applications in healthcare are rapidly advancing, transforming the way medical professionals diagnose, treat, and prevent diseases. In this rapidly evolving field, machine learning is poised to drive significant advancements in healthcare, improving patient outcomes and enhancing the overall healthcare experience.

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Amazon Web Services pitches customers on cloud savings, makes bigger push into applications

GeekWire

He also unveiled a series of new cloud applications that make AWS a player, if not a competitor, in some of the same sectors where its customers do business. ” Adam Selipsky announces AWS Supply Chain, one of Amazon’s new applications. Image via webcast.).

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Balance Speed, Experimentation, And Risk With FM&E Technology

Forrester IT

Learn how a new category of technology can help minimize those risks for your development teams. There's a certain amount of risk that comes with rapid innovation.

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Machine learning’s rise, applications, and challenges

Venture Beast

What is machine learning? This breakdown explains how machine learning works and its rise, applications, limitations, and challenges. Read More.

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Sysadmins: You're All Developers Now

Forrester IT

The learning experience is not one way. While you will learn much of this from developers, you will also impress on them key sysadmin principles like standardization, dependability, and security. In fact, the final evolution of this exchange is application and operations developers joining forces in a powerful mind-meld of talent.

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Cognitive Search Is The AI Version Of Enterprise Search

Forrester IT

Cognitive search is the new generation of enterprise search that uses artificial intelligence (AI) to return results that are more relevant to the user or embedded in an application issuing the search query. Cognitive search solutions are different because they: Read more Categories: AI. Cognitive Search.

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Five Factors That Make Deep Learning Different - Go Deep Baby!

Forrester IT

At the highest conceptual level, deep learning is no different from supervised machine learning. For example, developers can use Caffe, a popular deep-learning library, to train a model using thousands or millions of labeled images. Deep-learning algorithms do this themselves, without having to be programmed for it.

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