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MLSE looks to revolutionize sports experience with digital R&D lab

CIO

Digital solutions and data analytics are changing the world of sports entertainment at a rapid clip. From how players train, to how teams make strategic decisions during games, to how venues operate and fans engage, sports organizations are turning to software engineers and data scientists to help transform the sport experience.

Sport 202
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Enhancing customer care through deep machine learning at Travelers

CIO

This is kind of a team sport for us, so itâ??s that cover areas of software engineering, infrastructure, cybersecurity, and architecture, for instance. ve been on a mission to raise the water mark for the entire organization. We have about 13,000 employees through this set of training and itâ??s Plus, weâ??ve

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Rackspace’s Brian Lillie on the importance of leadership principles

CIO

Looking back, Lillie realized that as a father of four and 20 years spent coaching youth sports, this purpose statement has been central from early on. The troops represented four different organizations, brought together for the first time, and they had four different visions of success. “We

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5 ways organizations can lean into failure and transform it into success

LaunchDarkly

As software engineers, our industry may be competitive, but we need to remove the stigma associated with failing. This reaction occurs because there are often consequences for mistakes, which can impact us personally as well as the organizations we work for. ‘No,’ I replied, ‘I just spent $600,000 training him.

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Flight Price Predictor: Training Models to Pinpoint the Best Time for Booking

Altexsoft

concerts, sports competitions, festivals, terrorist attacks, natural disasters, political gatherings, epidemic outbursts, and. In this article, we’ll focus on a narrower task of finding and organizing airfare-related features. We used even more features to train our price predictor for FareBoom. Internal factors include.

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Evolving by Involving 

Honeycomb

The work we do ranges from support engineers who provide timely assistance to customers, to customer architects who dive deep into the technical stuff, to product training who educate folks on features old and new. Customer Success is a team sport. Eventually, though, teams’ mutual aid wasn’t enough.

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Lessons learned turning machine learning models into real products and services

O'Reilly Media - Data

With public figures like Intel’s CEO stating that every company needs a machine learning strategy or risks being left behind, it’s just a matter of time before machine learning enters your organization, too—if it hasn’t already. So what should an organization keep in mind before implementing a machine learning solution?