Algorithms of the Intelligent Web

Книга Algorithms of the Intelligent Web 2019-02-16

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By Haralambos Marmanis, Dmitry Babenko (Author's)

During my graduate school years I became acquainted with the field of machine learn-ing, and in particular the field of pattern recognition. The focus of my work was on mathematical modeling and numerical simulations, but the ability to recognize pat-terns in a large volume of data had obvious applications in many fields. The years that followed brought me closer to the subject of machine learning than I ever imagined. In 1999 I left academia and started working in industry. In one of my consulting projects, we were trying to identify the risk of heart failure for patients based (pri-marily) on their EKGs. In problems of that nature, an exact mathematical formula-tion is either unavailable or impractical to implement.

Modeling work (our software) had to rely on methods that could adopt their predictive capability based on a given number of patient records, whose risk of heart failure was already diagnosed by a cardiologist. In other words, we were looking for methods that could “learn” from their input. Meanwhile, during the ’90s, a confluence of events had driven the rapid growth of a new industry. The web became ubiquitous! Abiding by Moore’s law, CPUs kept getting faster and cheaper.

RAM modules, hard disks, and other computer compo-nents followed the same trends of capability improvement and cost reduction. In tandem, the bandwidth of a typical network connection kept increasing at the same time that it became more affordable. Moreover, robust technologies for developing web applications were coming to life and the proliferation of open source projects on every aspect of software engineering was accentuating that growth. All these fac-tors contributed to building the vast digital ecosystem that we today call the web.
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