Tech News

How to run R 4.0 in Docker — and 3 cool new R 4.0 features

There are some interesting changes and updates in R 4.0. Here I’ll take a look at three of them. Plus I’ll give you step-by-step instructions on installing R 4.0 so it won’t interfere with your existing R installation — by running R with Docker.

Docker is a platform for creating “containers” – completely self-contained, isolated environments on your computer. Think of them like a mini system on your system. They include their own operating system, and then anything you want to add to that – application software, scripts, data, etc. Containers are useful for a lot of things, but here

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R 4.0: 3 new features

Hi. I’m Sharon Machlis at IDG Communications, here with Episode 46 of Do More With R: Check out three new features in R 4.0 by running R and RStudio in a Docker container.

Docker is a platform for creating “containers” – completely self-contained, isolated environments on your computer. Think of them like a mini system on your system. They include their own operating system, and then anything you want to add to that – application software, scripts, data . . .. Containers are useful for a lot of things. I’ll be focusing on just one of those things today: testing

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How AIops improves application monitoring

IT operation teams use many tools to monitor, diagnose, and resolve system and application performance issues. In a recent survey of 1,300 IT professionals on the future of monitoring and AIops, 42 percent report using more than 10 monitoring tools; 19 percent use more than 25 tools.

That’s a lot of technology just to keep the lights on and provide the data required to monitor, alert, research, and resolve application incidents.

Monitoring tools are not one size fits all, especially for organizations running mission-critical applications in multicloud environments. As organizations invest in mobile apps, microservices, dataops, and data

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How to move data science into production

Deploying data science into production is still a big challenge. Not only does the deployed data science need to be updated frequently but available data sources and types change rapidly, as do the methods available for their analysis. This continuous growth of possibilities makes it very limiting to rely on carefully designed and agreed-upon standards or work solely within the framework of proprietary tools.

KNIME has always focused on delivering an open platform, integrating the latest data science developments by either adding our own extensions or providing wrappers around new data sources and tools. This allows data scientists to access

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Major R language update brings big changes

Version 4.0.0 of the R language for statistical computing has been released, with changes to the syntax of the language as well as features pertaining to error-checking and long vectors.

The upgrade was published on April 24. Source code for R 4.0.0 is accessible at cran.r-project.org. A GNU project, R has gathered steam with the rise of data science and machine learning, currently ranking 10th in the Tiobe Index of language popularity and seventh in the PyPL Popularity of Programming Language index.

Changes and features introduced in R 4.0.0 include:

  • A new syntax is offered for specifying _raw_
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The best free data science courses during quarantine

If you are locked down because of the COVID-19 pandemic, you just might have some extra time on your hands. Binging Netflix is all well and good, but perhaps you are getting tired of that and you would like to learn something new.

One of the most lucrative fields to open up in the last couple of years is data science. The resources I list below will help those technical enough to understand math at the level of statistics and differential calculus to incorporate machine learning into their skill sets. They might even help you start a new career as

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