Prototyping in Python for a large subset of people is NOT friendly. To quote a famous book or something; "My God, it's full of shapes!". Shapes whose shape matter, just not so much to the language and tooling you interface with them from. It's like trying to drive a 3d world from a 2d world :|
IMHO F# has the potential to be WAY more friendly for prototyping and more. It's all a matter of the libs.
> IMHO F# has the potential to be WAY more friendly for prototyping and more. It's all a matter of the libs.
Yeah, I've been dropping down to Visual Studio's F# console regularly to test things in a REPL-like environment.
Nowhere near the convenience of IPython though - I haven't come across anything way to import assemblies other than "#r /some/path/to/assembly.dll", which requires me to manually navigate through my project directories to find the correct folder/assembly. A notebook environment inside VS would be fantastic, too - rather than having a single line terminal-style input.
Re:Machine Learning for .NET
by smoothdeveloper on Friday December 21, 2018 @05:06AM
(#18732410)
https://fsprojects.github.io/Paket/paket-generate-load-scrip... is probably what you need if you enjoy using fsi and easily reference external libraries from script files.
In terms of things similar to numpy there's Accord.NET which is a very solid library but as far as I know, it's really the only mature/common one used.
Another thing is that .NET more or less focuses on traditional software development which I think can be considered cumbersome to work with if you're trying to test stuff quickly.
Little disclaimer, I'm not a data scientist but these are things I've noticed while deving with .NET so I'm not sure how much they actually apply to the day to day for a data scientist.