ml-coursera-python-assignments VS RStudio Server

check this out in particular. It's the week 4 homework from Ng's course, redone by someone to be in Python instead of Octave. It's got a built in grader, so you can grab the jupyter notebook, run it locally and it'll tell you when you've got the answer right. I'd recommend taking a crack at it, then when you figure out how to code it, take a look at that micrograd library and see how you could achieve something similar using an object oriented approach.

Python version of assignments which you can submit: https://github.com/dibgerge/ml-coursera-python-assignments

Basically title. I'm halfway thru the original Stanford University Machine Learning course by Andrew Ng, but instead of using the Octave/Matlab exercises, I went with a Python repo. Now, I know the new specialisation course came out and is updated with newer content, more relevant to the state of the industry today. I have the following choices:

A language is only worth learning if it is useful to know. But the only reason 99% of people would learn Octave is just to take that course lol. Besides, (a) the original course can be completed in Python using this repo, and now his new course is actually offered in Python.

FWIW there is a repo you can use to complete the first one in Python. I used it and can vouch that it works perfectly as advertised.

You can do them in python and submit them! https://github.com/dibgerge/ml-coursera-python-assignments

Andrew Ng ML-Coursera Assignments in Python

Last piece... Octave is super easy to get into. I don't personally think it's worth doing Python versions of the homework, but if you really can't stand screwing around with a new language, this repo has alternate versions of the homework to follow that will use Python instead. You can do either these or the original versions, so don't let the Octave scare you. You don't have to use it if you really don't want to, but... like I said, it's not a big deal either way, I just did it in Octave.

Specifically, I'm referring to this github repository: https://github.com/dibgerge/ml-coursera-python-assignments/blob/master/Exercise1/exercise1.ipynb. I'm currently doing Assignment 1.

This particular issue should be resolved in the latest daily builds of RStudio. The underlying issue here was a conda patch included in the conda-provided builds of R, which interfered with the way RStudio attempted to load R. Please see https://github.com/rstudio/rstudio/issues/13184#issuecomment... for more details.

It is a bug that was introduced in RStudio 2023.06.0 Build 421. See Error with 'cacheKey' in .rs.WorkingDataEnv and .rs.CachedDataEnv. The current advice is to ignore or add options(rstudio.help.showDataPreview = FALSE) to your ~/.Rprofile ... so RStudio can ignore it for you.

A quick google for details from other app: https://github.com/rstudio/rstudio/wiki/Writing-Good-Feature-Requests :)

solution found here: https://github.com/rstudio/rstudio/issues/9367

u/acemachine123, if you’re using Rmarkdown or Rprojects over a network drive, connected by VPN, it’s going to be slow like u/ThatDeadDude said. Best thing you can do is thumbs up the issue here https://github.com/rstudio/rstudio/issues/10417 and use an Rscript file instead.

Hey! I can not select the Noto Sans Mono font in RStudio's Editor Font options, despite it being installed in my system, as you can see in the picture. RStudio only offers me "Noto Color Emoji" instead. When looking for this online, I only found this: https://github.com/rstudio/rstudio/issues/9512, but I am not sure if this really a related issue. Or does RStudio not support TrueType fonts? I can't find anything about this after a quick search

Next (2023.03) changelog - https://github.com/rstudio/rstudio/blob/main/version/news/NEWS-2023.03.0-cherry-blossom.md .

for example in this post they have dark menus aswell