Hi everyone,
This week has been quite exciting has I had exams going on and I still managed to work on quite a lot.
I did manage to complete the use-case example for first week and get it up on the documentation as well.
Since a couple of weeks, we have also been discussing some big changes in DFFML architecture since we have just recently started to enhance our Python API. We discussed in our weekly sync-ups that we will make the hyper-parameters to enable tuning of models. This would be a side-quest that directly affects my project and so I'll be working to achieve this as well. We have already discussed it in detail and my mentor was kind enough to also provide me a patch to get me started. I worked out this patch and made some debugging ventures into the codebase and there were a few complications. Some things that I couldn't make sense on my own. I pinged my mentor over this and I'm hoping we will discuss it in our weekly sync-up tomorrow.
This week has been quite exciting has I had exams going on and I still managed to work on quite a lot.
What did you do this week?
Since we had our last weekly sync meeting at DFFML, yeah the one I talked about in my last check-in here, I have been thinking about and trying different things regarding the issues I was facing. Since my mentor was so kind to even give me a kick-start by explaining how I could test notebooks through a script and not manually test each notebook, I worked it out and it seems to do its job. Although, it still has some ways to go until it can be integrated into the CI due to some ipython kernel related errors which I'll be debugging soon but I plan to keep working on it while I also keep up with the weekly use-case examples that I have set out for each week.I did manage to complete the use-case example for first week and get it up on the documentation as well.
Since a couple of weeks, we have also been discussing some big changes in DFFML architecture since we have just recently started to enhance our Python API. We discussed in our weekly sync-ups that we will make the hyper-parameters to enable tuning of models. This would be a side-quest that directly affects my project and so I'll be working to achieve this as well. We have already discussed it in detail and my mentor was kind enough to also provide me a patch to get me started. I worked out this patch and made some debugging ventures into the codebase and there were a few complications. Some things that I couldn't make sense on my own. I pinged my mentor over this and I'm hoping we will discuss it in our weekly sync-up tomorrow.