Sharon Machlis

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About Sharon Machlis

Sharon is an award-winning journalist and data analyst who is equally at home analyzing data, coding tools for journalists, and covering technology. She is currently director of editorial data & analytics at Foundry (an IDG Inc. company), which publishes tech Web sites including Computerworld, CIO, PCWorld, and Macworld; and author of InfoWorld's Do More With R series .

Her book, Practical R for Mass Communication and Journalism, is available from publisher CRC Press and Amazon (you can see Six chapters free online).

Sharon is well known in the R community. She has taught workshops at ProPublica, and Investigative Reporters and Editors conferences and keynoted the 2020 European R User Meeting.

Sharon received an ASBPE national gold award for impact/investigative online excellence (see story) and two ASBPE national golds for best how-to article (see 2014 and 2017 winners) She was also named the Digital Analytics Association's top practitioner in 2021 for her work analyzing data at her job and in her community.

Sharon holds an Extra-class ham radio license and was honored by the Association of Radio Amateurs of Bosnia & Herzegovina "for extraordinary contribution to transmitting humanitarian messages of the citizens of Bosnia-Herzegovina" during the 1992-95 war.

Sharon's other hobbies include photography, travel, hiking, snowshoeing, crocheting, and classical piano. And, she's somewhat obsessed with both generative AI and the R programming language.

You can follow Sharon on Mastodon at and her searchable app with her Mastodon posts, as well as on LinkedIn. (She is not currently active on Twitter, but you can see her prior tweets at @sharon000.)

Sharon's Recent InfoWorld and Computerworld Articles

Maker of RStudio launches new R and Python IDE 2024-06-24

5 easy ways to run an LLM locally 2024-03-28

How to run R in Visual Studio Code 2024-02-15

Posit lays off R Markdown, knitr creator Yihui Xie 2024-01-05

8 ChatGPT tools for R programming 2023-12-21

Anthropic's Claude 2.1 LLM turbocharges performance, offers beta tool use 2023-11-21

Sharon's Data-Related Mastodon Posts

@srhrnkn Thanks for the possible explanation. But it was a foolish thing to write. That’s such a loaded and subjective attribute - what do you mean by ‘diverse city’? You can't just toss that into an article without explanation, and the only backup was the language issue. If the data was from a privately run study, she should have cited it. “Houston is one of the most diverse cities in the U.S.” would have been just fine for the purpose of the article. (2024-07-16 12:59:37)  >>

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The {greenR} 📦 “enables the quantification, analysis, and visualization of urban greenness within city networks. It leverages data from OpenStreetMap and is implemented as both an R package and a Shiny web application for user-friendly interaction. . . . greenR provides a new and scalable method to assign green indices to individual street segments.” By Sachit Mahajan, senior scientist, ETH Zurich
Package repo:
@rstats (2024-07-16 12:39:54)  >>

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"People would rather feel a certain way based on something completely false than look at facts and data," writes Christopher S. Penn in his Almost Timely Newsletter this week.

His example: People acting as if Covid has gone away when data *clearly* shows it hasn't. This crosses much of the political spectrum now.

Long Covid risks? Long-term organ damage? Most people now choose to ignore them.

(2024-07-15 16:36:49)  >>

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@simon's term “imitation intelligence” is such a great way to think about LLMs and generative AI. If we remember that models *appear* intelligent through token prediction and aren’t actually “smart” (yet?), we'll be better users. It's a useful framing for both their capabilities and limits.
His presentation is an interesting watch/read/listen, whether or not you use Python:

(2024-07-14 13:52:59)  >>

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