Hello,
as part of our studies, me and some friends have to contribute to an opensource project related to optimization. Your project seems particularly interesting.
Do you need help on a particular feature? On which subject do you advise us to work?
Hi @pierrechagn, I'm glad you're interested in this package, here there's a list of some features that are available to start working on in case you want to contribute, the suggested order:
The start point is to contribute to documentation so you get familiar with the package and its features, you can check some guidelines here #101
Enable Support for KerasRegressor and KerasClassifier tf wrapper
Add new adapters with more sophisticated rates update adapters
Add the configuration files to enable conda install #112
One big long-time feature is to remove DEAP (the current optimization engine) since it looks like it's not maintained any longer and it makes this package not compatible with python 3.10+. We must research which underlying optimization package can be used like NiaPy and migrate all the core features to use this package making the user API as close to the current one as possible
Hello, as part of our studies, me and some friends have to contribute to an opensource project related to optimization. Your project seems particularly interesting.
Do you need help on a particular feature? On which subject do you advise us to work?
Have a nice day, Pierre C.