Inspiration
As aspiring computer scientists, we spend no small amount of time sitting in front of a computer. Digital media is our bread and butter- as such, we decided to develop something that we would personally find useful in our lives as university students. We landed on Suggestify after much deliberation, but we agreed that all of us were running out of music to listen to and shows to watch during the quarantine. We are a team of individuals with mixed experience, two members with experience in web development and two members who are very new. As a result, the project was a teaching experience for everyone involved.
What it does
Suggestify is a web-based implementation of an app that serves as a sort of personalized dashboard that utilizes the power of Machine Learning in order to recommend a song/show for the user based on a simple quiz. Ideally, our site would collect user input in the form of quiz answers, and from that dataset, apply the ML algorithms in order to extrapolate and predict what kind of content the user wants to see/hear.
How we built it
Using a mixture of JavaScript, HTML, CSS, and an amalgam of APIs, we each got to work on our tasks. We divided the work into frontend/backend and got to work on each individual aspect of the project. The site manifested from a purely speculative endeavor into a real, tangible product all thanks to the tireless efforts of our team. Through a mix of brainstorming and sheer willpower, we managed to create something that resembled what we originally wanted.
Challenges I ran into
Actually making sure that all the moving pieces fit together was a considerable challenge that we certainly were not expecting when starting the project. We were met with unforeseeable roadblocks at every step of the way but were able to rely on each other for guidance as well as a helping hand. On top of that, the UI proved to be rather finicky along the way since certain elements did not work well with others. (I'm looking at you, immovable stars!)
Accomplishments that we're proud of
But at the same time, the UI design is something that we take great pride in. You would be proud too if you painstakingly selected every single color for each god-forsaken gradient, leaving the finished product line and lag free! Despite not having any prior experience with various APIs and Firebase, we managed to intuit how to utilize the provided features and add functionality.
What I learned
Speaking as someone who had very little experience with web-development before this project, I feel like I am horizons beyond where I was just a few days ago in terms of progress. Actually applying the knowledge from tutorials was far more effective at teaching than just watching those videos themselves.
What's next for Suggestify
There wasn't quite enough time to implement the show/movie suggestions quiz and prediction algorithm, but we've got high hopes for the future- when we plan to implement this feature and hopefully start to test it and iron out the wrinkles.
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