What did you do this week?

I met up with my mentor Hashim to discuss the automl branch. He pointed out some mistakes I made, which I have corrected and pushed to the latest commit.

What is coming up next?

Since this is the final week, I would hope to meet up with the rest of my mentors to tie up any loose ends and mark the completion of the GSOC project.

Did you get stuck anywhere?

Not really, there was slight trouble with the lack of a validation dataset for the tune function, but the current solution (splitting using sklearn) should be fine.

Apologies for the late blog post, school semester was hectic with numerous deadlines.

What did you do this week?

On the off time I had, attempted creating the ensemble model, to no avail unfortunately. Since it’s a stretch goal, I focused on schoolwork instead.

What is coming up next?

Since the final evaluation deadline is about a week away, I hope to get the final code review from mentors and tie up any loose ends in the  project.

Did you get stuck anywhere?

I was stuck at the ensemble model, which I guess I will put aside time as the deadline approaches. However, I could continue working on it after the GSOC period unofficially.  

What did you do this week?

Finalized the default/user-defined hyperparameters functionality for the AutoML model, added unit tests and a page of documentation.

What is coming up next?

I will be adding more unit tests to validate the performance of the model , and also explore the optional ensemble functionality. I’ve also requested a review from my mentors, will make changes if necessary if they request it.

Did you get stuck anywhere?

Default hyperparameters are a little troublesome, since they may not work with certain tuners, ie. Bayes optimization. Will consult with mentors to decide on how to handle that.

What did you do this week?

I’ve added the ability to pass hyperparameters to the AutoML model, and formulated some default values in case we decide to allow default hyperparameters for the final model. Besides that, progress is a little slow as my school semester has started.

What is coming up next?

I will continue watching closely for any feedback regarding the direction I should take the AutoML models’ tuning. Furthermore, I will be begin adding documentation for the AutoML model.

Did you get stuck anywhere?

Not really, hopefully it stays that way as I reach the final stretch.  

What did you do this week?

I completed the first iteration of the AutoML model and pushed it onto a new branch. The current model is able to take user-defined train/test datasets, and iterate over a list of user-defined models to return the best performing model. The tuning functionality has yet to be added as I am uncertain of the best way to approach tuning and await my mentor’s feedback.

What is coming up next?

I will be watching closely for any feedback regarding the direction I should take the AutoML models’ tuning. Otherwise, I will assume that model should be able to accept a user-defined set of hyperparameters, and work on incorporating that into the existing iteration.

Did you get stuck anywhere?

It was certainly challenging to get the AutoML model running as it is quite different from other existing DFFML models, but I managed to in the end and the rest should be quite smooth-sailing from here.