About: Data-scientist who loves to use #datascienceforgood, especially in ecology, energy and the environment. Bonsai, gardening, bikes and music when I'm not at a keyboard.
The language is called R.
There a strong convention of the tag #rstats being used in social media such as Twitter
Is there a preference/canonical tag on dev.to? Is there reason to merge the tags (if that is even possible)? Does it even really matter?
I don’t see any hashtag about R programming to follow. Not enough content about machine learning engineering in my opinion. Dev.to is build mainly for Software engineering topics. I don’t see anything related with the how you serve machine learning into a software. There’s not enough content in my opinion.
Well that's easy to fix. We just need to share some of our knowledge together :) @juliasilge and @colinfay both post semi-regularly, so you could follow them?
No i didn’t know about them. I am doing it right now. I will be happy to start writing about R. I just need to get better at it. For now i am doing some time series analysis. I am aiming to do more.
Great place to start. Have you heard of the fable package? I really like it for time series analysis.
Also, have you seen mara on twitter?
😳 Not sure they'll be coherent sans commentary…
"leaRning out loud: 📽 slides from EARL Boston"
maraaverick.rbind.io/2017/11/learni… #dataSciolist 😜14:02 PM - 05 Nov 2017
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She has this great talk about learning out loud. E.g. wrote it as you learn, and you'll learn more, and better.
Woaw i didn’t know about the fable package. I will definitely watch the talk. I will be inspired to do more. Learn more.
What’s a good good goal for knowing that you are an advanced R programmer:
As i do more stats because i am working with structured data. Doing data science and ML are more about working with non structural data and non parametric analysis universe. I don’t think you will gain deep knowledge in R. What’s your take?
Those are all great project ideas 👍
Unstructured data is definitely part of ml, but if you look at some of @juliasilge posts about tidymodels, there is a decent amount of work before the modeling to 'structure' the data at least a little. E.g data cleaning/pre-processing. Check out her post on the cocktails tidy Tuesday data set.
There is something else I would add, which is to 'deploy' R 'into production'. A hurdle that I often see is moving the work out of the users local machine and into the cloud. Writing about doing that really demonstrates an understanding of the language, purely because so few cloud providers make this simple, unlike things like PHP, python, java and JavaScript.
Something that really helped me understand functional approaches was reading the vignettes in the purrrr package, and a lot of the blog posts by Jenny Bryan.
Thank you, i will the articles and i will take a look at purrrr. You really should be a mentor lol. Take care, i am sending all my love from Haiti.
Ooooh i never even thought about checking the R tag. There is different content there! I would love it if the tags are merged, don't know if that is possible though.
R seems to not matter for DEV.to