Week 10: The Finale and the Future

Hi everyone! The week marks the end of the Senior Project. First of all, I want to say thank you to everyone who accompanied me on this journey. Thank you to Mr. Peter and Mr. Chen, my Senior Project Advisors, for giving me valuable feedback on my lessons. Thank you to Ms. Nagpal and this school for giving me this opportunity. And thank you to you, the readers and commenters, for your continued support.

Final Progress

Wrapping up the Senior Project, the brunt of this final week focused on creating the Paper and Poster for the upcoming Senior Project Presentation. The downside of creating a learning course in 10 weeks is that it’s difficult to get feedback since it’s impossible to expect volunteers to go through the entire course in just a couple of weeks. That’s why the initial plan was to have educators be the ones to give feedback since they’re more familiar with the field. Sadly, while the responses were positive, the sample size is still too small to perform any statistical analysis, so I had to rely on qualitative evaluation.

That said, at the beginning of this week, I shared my course on the Desmos Discord, and one person completed the entire course within just a few days. Collaborating with them gave me a fresh perspective on areas that could still be improved, such as adding a button to randomize variables whenever users become stuck in a local minimum. As I mentioned before, I hope to continue developing this project long after these 10 weeks and see how far I can take it.

Project Reflection

Ultimately, my project is about Neural Networks, and programming is necessary to dive deeper into the subject. This course can never replace traditional Machine Learning courses. However, I hope that it lowers the barrier of entry for students who would otherwise never engage with Machine Learning concepts and offers insights on key ideas for those starting their journey.

Desmos Implementation

The main focus of the course is on the Desmos implementation. And as I built the lessons around it, I’m amazed at how many concepts can be easily visualized for simple data sets that are just absent in traditional Machine Learning Courses.

From graphing the Loss functions of a Logistic Regression,

to visualizing neural networks with different activation functions.

Whenever I do a project, I always have a nagging feeling that it will turn out to be a worse version of something someone has already done. But after spending 10 weeks working on this project, I feel reassured of its value. I genuinely hope to continue developing this idea and eventually create a video series that can share these concepts with even more people.

Thank you again for all your support throughout this journey. If you enjoyed following this project, feel free to go back to Blog 0 and let my past self know how it all turned out.