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R Packages worth a look

转载自:https://analytixon.com/2018/12/21/r-packages-worth-a-look-1373/

Michael Laux


发表于 2018-12-21

Text Similarity (similr)Using brute-force string comparator algorithms, this package facilitates finding a particular string’s closest match amongst a target vector of strings.

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Distilled News

转载自:https://analytixon.com/2018/12/21/distilled-news-939/

Michael Laux


发表于 2018-12-21

Let’s Talk About AI Ethics; We’re On A Deadline

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The causal hype ratchet

转载自:https://andrewgelman.com/2018/12/21/causal-hype-ratchet/

Andrew


发表于 2018-12-21

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Six Steps to Master Machine Learning with Data Preparation

转载自:http://feedproxy.google.com/~r/kdnuggets-data-mining-analytics/~3/G6iZrf3MaO0/six-steps-master-machine-learning-data-preparation.html

Matt Mayo Editor


发表于 2018-12-21

By David Levinger, VP Dev and Cloud Operations at Paxata

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Transcribe speech in three new languages: French, Italian, and Brazilian Portuguese

转载自:https://aws.amazon.com/blogs/machine-learning/transcribe-speech-in-three-new-languages-french-italian-and-brazilian-portuguese/

Paul Zhao


发表于 2018-12-21

We’re excited to announce that Amazon Transcribe now supports automatic speech recognition in three new languages: French, Italian, and Brazilian Portuguese. These new languages expand upon the 5 languages already available in Amazon Transcribe: US English, US Spanish, Australian English, British English, and Canadian French.

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Feature engineering, Explained

转载自:http://feedproxy.google.com/~r/kdnuggets-data-mining-analytics/~3/xOwyTB5VU2Q/feature-engineering-explained.html

Dan Clark


发表于 2018-12-21

By Paweł Grabiński

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Machine Learning Explainability vs Interpretability: Two concepts that could help restore trust in AI

转载自:http://feedproxy.google.com/~r/kdnuggets-data-mining-analytics/~3/UShU74CYuEU/machine-learning-explainability-interpretability-ai.html

Dan Clark


发表于 2018-12-20

By Richard Gall, Packt

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Spelling 2.0: Improved Markdown and RStudio Support

转载自:http://feedproxy.google.com/~r/RBloggers/~3/fFCry9ivG20/

rOpenSci - open tools for open science


发表于 2018-12-20

We have released updates for the rOpenSci text analysis tools. This technote will highlight some of the major improvements in the spelling package and also the underlying hunspell package, which provides the spelling engine for the spelling package.

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R 3.5.2 now available

转载自:http://feedproxy.google.com/~r/RBloggers/~3/cnC759LsQc4/

David Smith


发表于 2018-12-20

R 3.5.2, the latest version of the R language for statistical computation and graphics from the R Foundation, was released today. (This release is codenamed “Eggshell Igloo”, likely in reference to this or this Peanuts cartoon.) Compared to R 3.5.1, this update includes only bug fixes, so R scripts and packages compatible with R 3.5.0 or R 3.5.1 should work without modification.

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How to Scrape Data from a JavaScript Website with R

转载自:http://feedproxy.google.com/~r/RBloggers/~3/77vaUcLm1kw/

Curiosity Killed the Cat


发表于 2018-12-20

In September 2017, I found myself working on a project that required odds data for football. At the time I didn’t know about resources such as Football-Data or the odds-api, so I decided to build a scraper to collect data directly from the bookmakers. However, most of them used JavaScript to display their odds, so I couldn’t collect the data with R and rvest alone. In this article, I’ll demonstrate how PhantomJS can be used with R to scrape JS-rendered content from the web.

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