|4 months ago||12 days ago|
|MIT License||MIT License|
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Julia vs R/Python
5 projects | reddit.com/r/datascience | 20 Mar 2021
10-100x speed increase was not an exaggeration for me. With julia I was able to run things quickly on my own machine which I had been running on a compute cluster. I agree that numba could be just as fast as julia. I also just saw that you can run that DE library from julia that I like so much from python using this package. https://github.com/SciML/diffeqpy
What are some alternatives?
DiffEqBase.jl - The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
csvzip - A standalone CLI tool to reduce CSVs size by converting categorical columns in a list of unique integers.
DifferentialEquations.jl - Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components