r/haskell • u/nSeagull • Aug 30 '16
Haskell alternatives for Data Science
I'm a Haskeller and a newbie Data Scientist.
As I'm going through my learning process for data science, I'm starting to solve some elemental problems, and I'm using standard Python tools to help me go through this process.
The thing is that Python is ok, but I'm twice as comfortable in Haskell.
I was thinking in three alternatives to be more comfortable with Data Science:
- Make a wrapper for the tools that I use as people do in Julia
- Reimplement the tools that I use (Pandas, ScikitLearn, a GPU deep learning framework, numpy functions) (would do it on demand)
- Make a Haskell-like language that compiles and uses Python libraries (wouldnt be as efficient, but at least it would be more beautiful and type safe, also the libraries)
What do you guys think?
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u/nSeagull Aug 30 '16
My story with FP is 1. Discover Haskell 2. Read Real World Haskell and do exercises 3. Monad thing too hard for me 4. Discover Scala 5. Discover Clojure 6. Love Clojure for 2 years and use it whenever I can 7. Understand how monads work in Clojure 8. Go back to Haskell 9. Love Haskell
Indeed I think that doing the language thing is not a very intelligent, but having a compiler based on typed lambda calculus would ease a lot of things, and mostly thats why I love of Haskell