Vikos is a library for supervised training of parameterized, regression, and classification models
- Model representations, cost functions, and optimization algorithms can be changed independently of each other.
- Generics: Not committed to a particular data structure for inputs, targets, etc.
- If the design goals above can only be achieved by sacrificing performance, so be it.
Just starting to get the traits right, by continuously trying new use cases and implementing the learning algorithms. If you are looking for more mature rust libraries in the domain of ML, you might want to check out:
-
Install the rust package manager
cargo
. Goto rustup and follow the instructions on the page (in my experience this works fine for Windows, Ubuntu and OS X). -
Run
cargo new --bin hello_vikos
. -
switch to the
hello_vikos
directory. -
Run
cargo run
to execute the hello world program. -
Edit the
Cargo.toml
file. Addvikos = "0.2"
to your dependencies. The file should now look somewhat like this:[package] name = "hello_vikos" version = "0.2" authors = ["..."] [dependencies] vikos = "0.1.8"
-
Insert
use vikos;
at the first line insrc/main.rs
-
You can now start replacing code in
main
with code from the tutorial.fn main() { /* tutorial code goes here */ }
Thanks to the folks of docs.rs for building and hosting the documentation!
Want to help out? Just create an issue, pull request or contact [email protected].