Hi everyone,

It's a pleasure to let you know that I have completed the project with all the requirements and more! It has been an amazing journey, from learning to getting amazing mentorship from John Andersen, to getting to know a great community. This has really been a wild journey!

If you would like to know more about my project, here is the Final Report.

Hi everyone,
This is the 11th weekly check-in. Everything went as planned.

What did you do this week?

This week, I have wrapped all tasks related to my project in DFFML. The multi output PR got merged as well. The 'Tuning Models' PR also got reviewed and I just need another rebase to get it merged as well.

What is coming up next?

Hopefully the 'Tuning Models' PR will get merged in the weekly sync tonight. And that will wrap up GSoC for me :D

Did you get stuck anywhere?

Not really, I made sure to get things right with mentors when I could.

Hi everyone,
This is the 10th weekly check-in and I had totally forgotten about writing a blog since this week was quite hectic, with project defenses going on in the university and deadlines to meet for GSoC.

What did you do this week?

We finally got in support for mutable config in models. I have been working on the final use-case of my project ie. 'Tuning Models'. For this, I showed how to tune models by mutating their values in the configs. I also added a parameter grid module so users can define a grid and DFFML helps them tune their models by training and testing the models with the data to find the best hyper-parameters and score. My mentor had also asked to change the way accuracy works in general. I forced accuracy to take prediction features so scorers don't access the model's features, and forced theses features to the last argument of the scorers.

What is coming up next?

I will be finishing these tasks and wait on reviews and hopefully get these PR's merged ASAP.

Did you get stuck anywhere?

Yeah, there were some issues with http, my mentor helped me get rid of those.

Hi everyone,
This is the 9th weekly check-in and things seemed to be going as planned so far, however, it's time to deal with the elephant in the room ie. the "Tuning Models" use-case we don't have support for.

What did you do this week?

As it turns out, my peer was also working on scikit. He introduced scorers into the code-base which resulted in huge rebase for me. I rebased everything multi-output models related and merged conflicts. However, I had to also add multi-output support to the scorers now, and that I did. I made it so that the scikit scorers could be used for multi-output models. I also added support for the couple of 'native' scorer implementations that we added in DFFML but I wasn't convinced of the implementation myself as we were just using mean of all the accuracies or scores. I discussed it with my mentor and we decided to go with just the sickit scorers. My mentor also suggested me other changes in the weekly sync we had yesterday.

What is coming up next?

I will be working on the changes suggested by my mentor and get the PR reviewed in detail. My mentor would also help figure out the dependencies of the use-case "Tuning models" to make configs mutable etc. so that I can proceed.

Did you get stuck anywhere?

Not really.

Hi everyone,
This is the 8th weekly check-in and things got a little off the timeline as we didn't have a weekly sync-up meeting last week but I think I have things back on track now hopefully.

What did you do this week?

I finished working on support for multi-output models. I decided to go with the multioutput scikit wrappers rather than using the native support of some models which would essentially add an extra layer to the structure of our models in DFFML. In the current structure, DFFML acts as if the models really do support multi-output natively rather than having separate entry-points as discussed previously. I had been waiting for the weekly meeting to discuss this before implementing however, since the last meeting didn't take place, I decided to go ahead and implement it and discuss it in the next meeting with the sample code.

What is coming up next?

Hopefully my mentor will approve of the different approach I went for in the coming sync-up and we get it merged soon. I'll start working in the multi-output model use-cases in that case.

Did you get stuck anywhere?

I wasn't really stuck but wanted to be sure if the approach I went for was indeed the right thing to do.