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Amazon Personalize launches new recipes supporting larger item catalogs with lower latency

AWS Machine Learning - AI

In this post, we summarize the new enhancements, and guide you through the process of training a model and providing recommendations for your users. Benefits of new recipes The new recipes offer enhancements in scalability, latency, model performance, and functionality. Now you’re ready to train your model.

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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. On business transformation: We perform around our current business and want to meet to be able to deliver results. But we have to bring in the right talent. 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. You don’t earn the right to innovate if you can’t keep the trains running on time.” The first message he gave to the class: “IT operations is job one.

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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. We used even more features to train our price predictor for FareBoom. A lot of great things — like better performance, higher accuracy and speed, and less memory required. Internal factors include.

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A year on from Russia’s invasion, Ukrainian startups show astounding resilience

TechCrunch

Blocksport Blocksport builds Web3-ready platform solutions for the professional sports and entertainment industry to enable tokenization use cases for their fan community. Its 2,000 staff work on software and product design for corporate giants including BNY Mellon and Havas, and moved its offices in the Western part of Ukraine.

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Lessons learned turning machine learning models into real products and services

O'Reilly Media - Data

A model that recommends what sports programs to watch, for example, would need to consider that the Super Bowl is huge in the U.S., how it’s actually performing in production—is very tricky, and even the industry’s most experienced teams can get it wrong. Sometimes, the need to localize models is obvious.

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Meet the Coach: Magnus Kollberg

Agile42

After university, where I graduated with an MSc in Computer Engineering I spend some years as a software engineer in the pulp and paper process industry, did a lot of traveling as well as some teaching, all in all very interesting times. What was your path leading you to Agility and to agile42?