I'm a big Go fan, but this is the first time I've seen someone recommend Go for data science. After looking at this cheat sheet you've got me convinced though. Would you mind pointing me to any other less cheat sheet style and more in depth examples that you particularly like?
Working on it. Part of my goal for 2018 is to write a lot more soft documentation - tutorials etc.
Go is quite straightforwards though - WYSIWYG for the most parts, hence you probably won't find a lot of sexy tutorials. Almost everything is just a loop away, and in the next version of Gorgonia, even more native looping capability is coming
- Jupyter + Pandas for exploratory work, quickly define a model
- Go (Gonum/Gorgonia) for production quality work. (here's a cheatsheet: https://www.cheatography.com/chewxy/cheat-sheets/data-scienc... . Additional write-up on why Go: https://blog.chewxy.com/2017/11/02/go-for-data-science/)
I echo ms013's comment very much. Everything is just tools. More important to understand the math and domain