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anytime – dates in R

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

aghaynes


发表于 2018-11-08

I just saw an announcement on R Bloggers about the anytime package. It looks to be a very handy package to convert dates in pretty much any format to Date or POSIX classes, without the need to define the format – it’s guessed by an underlying C++ library.

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Best Practices for Using Notebooks for Data Science

转载自:http://feedproxy.google.com/~r/kdnuggets-data-mining-analytics/~3/8OGo19-SjZU/best-practices-notebooks-data-science.html

Matt Mayo Editor


发表于 2018-11-08

By Armin Wasicek, Sumo Logic

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Carlos: ‘Everything Dataquest showed me, I use in my new job’

转载自:https://www.dataquest.io/blog/dataquest-job-success-carlos/

Charlie Custer


发表于 2018-11-08

When Carlos Cutillas de Frutos graduated from the Business Administration program at CUNEF in Madrid, he knew he wanted to add something extra to his business skill set. He quickly settled on data science, because he enjoyed statistics and he knew there was a lot of potential for growth there. But he still had a big problem: he had virtually no experience with programming.

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AzureR: R packages to control Azure services

转载自:https://blog.revolutionanalytics.com/2018/11/azurer-intro.html

Hong Ooi


发表于 2018-11-08

by Hong Ooi, senior data scientist, Microsoft Azure

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10 Free Must-See Courses for Machine Learning and Data Science

转载自:http://feedproxy.google.com/~r/kdnuggets-data-mining-analytics/~3/HAM7u7P-j04/10-free-must-see-courses-machine-learning-data-science.html

Matthew Mayo


发表于 2018-11-08

This is a collection of free machine learning and data science courses to kick off your winter learning season. Courses range from introductory machine learning to deep learning to natural language processing and beyond.

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Distilled News

转载自:https://analytixon.com/2018/11/08/distilled-news-904/

Michael Laux


发表于 2018-11-08

TRE: A Regex Engine with Approximate Matching

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Hilary Mason and Gilad Lotan to Keynote at MADS 2019

转载自:http://feedproxy.google.com/~r/kdnuggets-data-mining-analytics/~3/g6-zVP3pdrc/mads-hilary-mason-gilad-lotan-keynote-2019.html

Matt Mayo Editor


发表于 2018-11-08

As consumers demand more personalized communications, experiences, and products; and internal stakeholders require more predictive intelligence to inform decisions, a disciplined approach to analytics and data science are the keys to unlocking opportunity and growth. || |Hilary MasonGM of Machine Learning, Cloudera and Former Chief Data ScientistBitly| || |Gilad LotanVP Head of Data ScienceBuzzFeed| || |Avinash KaushikDigital Marketing Evangelist and Author ofWeb Analytics 2.0 and Web Analytics: An Hour A Day|

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Latest Trends in Computer Vision Technology and Applications

转载自:http://feedproxy.google.com/~r/kdnuggets-data-mining-analytics/~3/lFkoLsxJEoI/trends-computer-vision-technology-applications.html

Dan Clark


发表于 2018-11-07

By Valeryia Shchutskaya, InData Labs.

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Working with US Census Data in R

转载自:http://feedproxy.google.com/~r/RBloggers/~3/XuZBG98mUtc/

David Smith


发表于 2018-11-07

If you need data about the American populace, there’s no source more canonical than the US Census Bureau. The bureau publishes a wide range of public sets, and not just from the main Census conducted every 10 years: there are more than 100 additional surveys and programs published as well. To help R users access this rich source of data, Ari Lamstein and Logan Powell have published A Guide to Working with US Census Data in R, a publication of the R Consortium Census Working Group.

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anytime 0.3.2

转载自:http://feedproxy.google.com/~r/RBloggers/~3/KI5cCBX4Qkc/

Thinking inside the box


发表于 2018-11-07

A new minor release of the anytime package arrived on CRAN this morning. This is the thirteenth release, and the first since July as the package has gotten feature-complete.

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