Hello all! Is there any documentation about tuning neural networks (or other machine learning algorithms) hyperparameters using Kedro? I don't really know where to start. Sure, I want to create a new pipeline which will be given a training and validation set. I was wondering about the best way(s) to proceed. This is what I want: • I would like the pipeline to output a text file or table containing the validation loss for all hyperaparameters combinations. • Ideally, I would like to track the experiments (so if I change my hyperparameters grid, I want to still have access to former results). • Could MLFlow help me with this? I know that Kedro has its own experiment tracking system. • Could the Kedro parameters help me achieve my goal? • It would be nice to visualize the results in Kedro viz. Thanks!

Answer to some of these questions. For tracking, you can use Kedro's own experiment tracking, MLflow would also work. Checkout the kedro-mlflow plugin which is maintained by our community.

Mostly tables showing the loss for each hyperparameter combination.

that's great:) there is a #plugins-integrations channel and plenty of kedro-mlflow users and the authors of the plugin in this Slack group.

For hypermarams search I don't think that there's a golden/community approved standard yet. I'd love to hear some ideas or approaches people use/try to use

Hi everyone, It’s been a while ! Regarding Hyperparameter Search: I’m looking into using Optuna… Has any of you guys used it in a kedro pipeline + kedro-mlflow ? 🙂 Have a nice week-end, Cheers M