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R Packages worth a look

转载自:https://advanceddataanalytics.net/2018/10/05/r-packages-worth-a-look-1293/

Michael Laux


发表于 2018-10-04

Send Emails using ‘Mailgun’ (IMmailgun)Send emails using the ‘mailgun’ api. To use this package you will need an account from <https://w …

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UnitedHealth Group: Sr .Net Web Developer, UHC E&I [Indianapolis, IN or Green Bay, WI]

转载自:http://feedproxy.google.com/~r/kdnuggets-data-mining-analytics/~3/XuZZrTzESxc/10-04-unitedhealth-group-web-developer.html

Matt Mayo Editor


发表于 2018-10-04

At: UnitedHealth GroupLocation: Indianapolis, IN or Green Bay, WI Web: www.unitedhealthgroup.comPosition: Senior .Net Web Developer, UHC E&I

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Top 10 Mistakes to Avoid to Master Data Science

转载自:https://dimensionless.in/top-10-mistakes-avoid-master-data-science/

Kartik Singh


发表于 2018-10-04

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“Six Signs of Scientism”: where I disagree with Haack

转载自:https://andrewgelman.com/2018/10/04/six-signs-scientism-disagree-haack/

Andrew


发表于 2018-10-04

I came across this article, “Six Signs of Scientism,” by philosopher Susan Haack from 2009. I think I’m in general agreement with Haack’s views—science has made amazing progress over the centuries but “like all human enterprises, science is ineradicably is fallible and imperfect. At best its progress is ragged, uneven, and unpredictable; moreover, much scientific work is unimaginative or banal, some is weak or careless, and some is outright corrupt . . .”—and I’ll go with her definition of “scientism” as “a kind of over-enthusiastic and uncritically deferential attitude towards science, an inability to see or an unwillingness to acknowledge its fallibility, its limitations, and its potential dangers.”

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Big Data Day Camp: Big Data Tools & Techniques (October 25-26)

转载自:http://feedproxy.google.com/~r/kdnuggets-data-mining-analytics/~3/2HrJ5AaIBw4/ucsd-big-data-day-camp-tools-techniques-october.html

Matt Mayo Editor


发表于 2018-10-04

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Deep Learning Without Labels

转载自:https://blogs.technet.microsoft.com/machinelearning/2018/10/03/deep-learning-without-labels/

ML Blog Team


发表于 2018-10-03

Announcing new open source contributions to the Apache Spark community for creating deep, distributed, object detectors – without a single human-generated label

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Linear Regression in the Wild

转载自:http://feedproxy.google.com/~r/kdnuggets-data-mining-analytics/~3/kzcxBoGGsKs/linear-regression-wild.html

Dan Clark


发表于 2018-10-03

By Yoel Zeldes, Algorithms Engineer at Taboola.

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How to use common workflows on Amazon SageMaker notebook instances

转载自:https://aws.amazon.com/blogs/machine-learning/how-to-use-common-workflows-on-amazon-sagemaker-notebook-instances/

John Calhoun


发表于 2018-10-03

Amazon SageMaker notebook instances provide a scalable cloud based development environment to do data science and machine learning. This blog post will show common workflows to make you more productive and effective.

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Data Science at Northwestern

转载自:http://feedproxy.google.com/~r/kdnuggets-data-mining-analytics/~3/6nOPN383MzE/northwestern-ms-data-science.html

Matt Mayo Editor


发表于 2018-10-03

Advance your data-driven career at Northwestern

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R Packages worth a look

转载自:https://advanceddataanalytics.net/2018/10/04/r-packages-worth-a-look-1292/

Michael Laux


发表于 2018-10-03

Quantity Calculus for R Vectors (quantities)Integration of the ‘units’ and ‘errors’ packages for a complete quantity calculus system for R vectors, matrices and arrays, with automatic propagation …

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SunJackson

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