Blog post #3 – Working on ML input

My team and I continue to chip away at this project. Although, we have had some difficulties along the way, today was a breakthrough daysimply due to the fact that we overcame many of these issues. Furthermore, we have been working fairly well as a team and help each other resolve with bugs/problems we come across.

Although we have not gotten to actually constructing our machine learning model yet, we have completed the portion where we prepare the input that will eventually server as the ML input. The biggest hurdle we faced was working with continuous integration on Git. We set up CI to help us in the long run, so that we can spot bugs before we make permanent branch changes but it proved to be time consuming in debugging the CI itself. But we solved the issue today and began integrating our branches.

Overall, we have been good progress. We plan to complete constructing a base machine learning model by end of this sprint, after which we can begin training using our converted inputs. Machine learning is proving to be exciting and I am hoping to learn more on the topic going into the next sprint!

Blog post #2 – Project progress!

This week marks my 4th week in this Capstone course and so far things are going pretty good. My team, with whom I am creating this project with, all seem to be excited about our project: a music genre classifier that using a machine trained model!

My team and I are uninitiated when it comes to machine learning so we had some trouble setting up a functional project plan. However, it turns out that is nothing a little research cant solve! I am excited to get a Minimum Viable Product up and running to see the fruits of our labor. We have decided to go with pytorch for the ML framework and that seems to have been the right call in the short time that I have used it. This is primarily due to the fact that we will be utilizing python as our primary language in this project So seeing as though pytorch was a ML library built specifically for python, we abandoned our initial decision to use tensor flow for the more friendly framework.

Being as this will be my final class in this CS program, I am excited to add machine learning to my list of versed technologies. Although there is ways to go before we can began seeing results, so until then, our work continues!