This week, I was mainly focused on editing the slides and preparing for the presentation, which I presented on Monday. I appreciated the feedback and questions that we received from the Instructors and classmates, and particularly the pushback on the false positive rate, which I feel is a valid concern. As an aside, I felt that some of the feedback I received saying that I did not know the material well, or that I was underprepared, was unwarranted, as I had spent a substantial amount of time on the presentation. However, perhaps due to being too softspoken and having technical difficulties during the presentation, I was not able to reflect that.
Additionally, I have also spent a bit of time doing research on object detection algorithms for the implementation of the walk sign detection.
I am currently on schedule, as our team has put aside time in our schedule for the first four weeks, to specifically do research and flesh out our design (as well as prepare for presentations) before we start implementing.
Since I have limited experience with ML, I really want to get a head start on the material and implementation. In this upcoming week, I will be doing more research, as well as working with Eshita to find/create a dataset for walk signs fo the ML model that I will implement. Additionally, I also hope to set up a github repo and start writing down some code, if possible. Lastly, I will talk with my teammates to see if AWS may be needed for model training, and talk with the TAs and professor if we do to set that up.