23
submitted 2 days ago by jupyter@lemmy.ml to c/privacy@lemmy.ml

I'd like to make an informed decision on extensions I install. Usually I read about people caring about browser extensions. I install extensions in vscode, in zed, gnome, kde and probably in a lot of other tools like bash as well.

Usually, I do not think much about security/ privacy. I only install what I want/ need and delete what I do not need.

How can I judge which extension to install and which not? There are extensions releasing builds regularly but the last release of public code on github was years ago. Downloads and stars give a hint on popularity. With popularity the people who will look into the code increases but if there's no code, there's nothing to look into. And just because it's not popular, it doesn't necessarily mean it's bad software.

How do you judge which extension to install?

[-] jupyter@lemmy.ml 1 points 7 months ago* (last edited 7 months ago)

thanks! That's good to go through. knowing plots is always good

16

I’m starting as data analyst (roughly bachelor level). My responsibility will be to analyze time series data and classify agents and write reports. I won’t be responsible for the database management. It’s likely that I have to use R because my colleagues use R. I guess I may use python if it’s more appropriate.

Which books and other things can you guys recommend? What should I avoid?

[-] jupyter@lemmy.ml 1 points 7 months ago

that's good advice, yet I have no direct contacts information and there's still time until I start with the position.

I am proficient in time series data analysis and programming in R, python and julia. I may extend packages and functions as I need. I may properly debug functions and find bottlenecks in code by profiling it. Regarding reports, I'm capable of writing high quality reports, for professionals and for the general public. I understand the underlying math and statistics and am able to extend models properly for adjustments in theory.

I have deficiencies in advanced classification models and in general there's so much information out there that I'm not sure how much I actually know. I guess revisiting statistics might never be wrong

jupyter

joined 7 months ago