41–50 of 177 posts
Mathematics. Which branch of math is domain dependent. Stats come up everywhere. Graphs do too. In addition to baseline math, you really need to understand the problem domain and goals of the analysis. Languages and libraries are just tools: knowing APIs doesn’t tell you at all how to solve a problem. They just give you things to throw at a problem. You need to know a few tools, but to be honest, they’re easy and you…
- 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
My toolkit hasn't changed since 2016: - 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 t…
My toolkit hasn't changed since 2016: - 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 t…
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?
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
a lot of people using spark?
Mathematics. Which branch of math is domain dependent. Stats come up everywhere. Graphs do too. In addition to baseline math, you really need to understand the problem domain and goals of the analysis. Languages and libraries are just tools: knowing APIs doesn’t tell you at all how to solve a problem. They just give you things to throw at a problem. You need to know a few tools, but to be honest, they’re easy and you…
https://towardsdatascience.com/data-is-a-stakeholder-31bfdb6...
(Disclaimer: I wrote the post at the above link).
If you have a sound design you can still create a huge amount of value even with a very simple technical toolset. By the same token, you can have the biggest, baddest toolset in the world and still end up with a failed implementation if you have bad design.
There are resources out there for learning good design. This is a great introduction and points to many other good materials:
https://www.amazon.com/Design-Essays-Computer-Scientist/dp/0...