An ML introduction to ndarray
Happy RustFest!
It's my pleasure to welcome you to the ML introduction to ndarray workshop!
The material is structured as a series of exercises, or koans, that you can find in the src/koans directory.
You can get started with
git clone [email protected]:LukeMathWalker/ndarray-koans.git
cd ndarray-koans
cargo runFollow the instructions shown in the terminal to start the first exercise.
Enjoy!
Requirements
Software
- Rust 1.38 (or higher) with
cargo- Check link for installation instruction if you don't have Rust installed on your machine
- If you already have Rust installed, run
rustc --versionto check the version. Runrustup updateif you need to update your toolchain (if you installed usingrustup)
There are some Jupyter notebooks that you will have to run to perform some data visualisations. Install
instructions for those are in python/README.md.
Knowledge
A basic knowledge of Rust is assumed (the first half of the book?). If you run into any issue with the language, please ping me and we'll sort it together!
References
Throughout the workshop, the following resources might turn out to be useful:
- Scientific Computing: A Rust adventure: an
introduction to
ndarraythat assumes no Rust knowledge (not complete yet 😅); - The Rust Book;
- Docs for the crates in the
ndarrayecosystem: - If you are familiar with Python's
NumPy, checkndarrayforNumPyusers.