| Author | Stephan Sahm |
|---|---|
| stephan.sahm@jolin.io |
Learn how to easily speed up Python with Julia.
- Introduction to Julia I: calling Julia from Python
- Introduction to Julia II: Pluto, pure Julia
- Simulation example: Python vs Cython vs C++ vs Julia
The links above will spawn jupyter notebook on mybinder.org. One CPU and 1-2 GB memory, just for you, thanks to the supporters of mybinder.org.
If mybinder.org is down, or you like to have things locally, you can do so easily. (Note that the first run can take 5 minutes, after that it is instantly loaded from cache).
Install docker and jupyter-repo2docker, and then create your own local environment with the following command.
jupyter-repo2docker https://github.com/jolin-io/workshop-accelerate-Python-with-Julia
Jolin.io helps companies develop energy-efficient AI and data applications with ease. We specialize in machine learning, Big Data, and real-time pipelines, with support for the programming languages Python, R and Julia.