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| August 15, 2016
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Article | April 24, 2020
Feature engineering is the process of extracting new variables by transforming raw data to improve the predictability of a machine learning model. But feature engineering is not just this kind of simple translation of categories like names or colors into numbers. The following section includes a collection of different kinds of engineering approaches that go beyond a translation of categories into numbers and address needs such as transforming numbers into categories or filtering data points due to missing or false data.
In this fortnightly blog, ICE's Director of Policy Chris Richards looks at developing policy landscape for infrastructure, what decisions mean, and their implications, so that infrastructure professionals can play their part in shaping the discussion.
Cloud Infrastructure and Engineering Leader, Pulumi announced version 2.0 of its platform. The new version comes equipped with policy, testing, and architecture as code to infrastructure provisioning. The users are calling these updates as superpowers that the company has added to the platform. The new capabilities of Pulumi 2.0 enable developers to accelerate application delivery and infrastructure to any private, public, or hybrid cloud with increased confidence and built-in governance.
When the Tamina Bridge in the Swiss Alps was first proposed, the engineers were uncertain how they would create a bridge that spanned two different heights at each end of the valley, at a height of 220m (772 feet) above ground. Yet despite these challenges, the bridge was completed a year ahead of schedule in just four years – mainly due to the efficiencies that Building Information Modelling (BIM) provided. While the name may inadvertently imply that only buildings can benefit, BIM offers a host of advantages when designing and building bridges as well.
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