SciMLTutorials.jl: Tutorials for Scientific Machine Learning and Differential Equations
SciMLTutorials.jl holds PDFs, webpages, and interactive Jupyter notebooks showing how to utilize the software in the SciML Scientific Machine Learning ecosystem. This set of tutorials was made to complement the documentation and the devdocs by providing practical examples of the concepts. For more details, please consult the docs.
To run the tutorials interactively via Jupyter notebooks, install the package and open the tutorials like:
using Pkg pkg"add https://github.com/SciML/SciMLTutorials.jl" using SciMLTutorials SciMLTutorials.open_notebooks()
Table of Contents
- Exercise Sheets
- Modeling Examples
- Advanced ODE Features
- Model Inference
- Type Handling
First of all, make sure that your current directory is
of the files are generated from the Weave.jl files in the
To run the generation process, do for example:
using Pkg, SciMLTutorials cd(joinpath(dirname(pathof(SciMLTutorials)), "..")) Pkg.pkg"activate ." Pkg.pkg"instantiate" SciMLTutorials.weave_file("introduction","01-ode_introduction.jmd")
To generate all of the notebooks, do:
If you add new tutorials which require new packages, simply updating your local environment will change the project and manifest files. When this occurs, the updated environment files should be included in the PR.