Why is Python so fashionable in machine learning? - page 8
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I did it. )
Yeah, and it turns out that the python from the official site is installed as an upgrade to the python folder from MS. See post #63 with funny picture))
What a nightmare!
What's the point of having a programming system that qualified people can't install in three days?
And the value is in the packages, and the packages must correspond to a very specific python, including revisions of this and that...
It's time to rename the topic "How to Install Python".
What a nightmare!
What's the point of having a programming system that qualified people can't install in three days?
And the value is in the packages, and the packages should correspond to quite a certain python, including revisions of this and that...
Yeah, and it turns out that the python from the official site is installed as an upgrade to the python folder from MS. See post #63 with funny picture))
VS has Python support. That's what it installs if you turn it on.
I see, the curve closed in a circle. From here on, we'll go in the same rut as the SS?
You started with Python and ended with Sharp. So what's the conclusion?
Python resembles pseudocode in its simplicity. But it works. C#, C++ require more details and consequently more time to learn and develop.
There is no nightmare there and packages are installed simply. It is not even necessary to download them beforehand.
Let's compare, with what everyone wants to have in R
1. there is a site (today there are two, but equivalent) developers who support R.
2. The site has all the releases with the differences
3. there are a huge number of packages that are listed on R sites with subject headings.
4. There is a mechanism for matching R releases and packages
5. Package documentation always corresponds exactly to the version of the package
6. There is a mechanism for committing the R release and the packages corresponding to that release.
7. There are tools which allow collaborative development and subsequent code execution on many computers
8. There is an R magazine with publications and innovations
9. There is an R-blog which has a feed
10. Functional completeness of tools in relation to the development and use of models and statistics.
In my mind, only having solutions to all of these issues can inform decisions about industrial use of python.
PS.
And when I wrote "nightmare", installing R is 5 minutes, without any options.
I see, the curve closed in a circle. We'll go further in the same rut as the SS?
What is SS?
How about it, San Sanych is our favorite )) SS