A door to many opportunities
Neural Networks have become the hot new buzzword for machine learning. Novel to the world of Computer Science and the AI consumer industry, the talk of machine learning has been turning heads recently. Giving computers the ability to learn is bewildering useful beyond our own comprehension. But will the implementation of computers with the ability to “learn” take over jobs? Perhaps, our lives? Well, let’s not get too far ahead and focus on the small fun projects where we can utilize machine learning and neural networks.
My capstone project: Top-n Music Genre Classification Neural Network – The name says it all. A project that will classify a number (n) music genre using a neural network. Who needs such a thing? Well, if you are not an avid music listener, this might not even nudge you interest. But to those who appreciated being able to categorize their music playlists on Spotify, this might be for you. Big music streaming services like Spotify, Apple Music, Amazon Music, etc. are leaning into machine learning in order to give users the best listening experience possible. This means if you play a song, similar songs will continue to play automatically. This means while you sip hot cider during the morning of Christmas, opening gifts from loved ones while listening to Mariah Carey, Metallica won’t be on queue waiting to turn your children into a bunch of metal-heads. Although, that wouldn’t be the worst Christmas present, would it?
Explaining how a neural network is complicated, in-fact if you want to learn right now, then go do a few google searches or maybe watch a couple of Stanford’s CS231 lectures. But here is a brief description of how it works. A neural network is like a Blackbox function, no one really can know what is happening. Given lots and lots of data however, through multiple layers where each layer consists of many neurons, input information is essentially processed, changing the weight and biases of these neurons based on the expected output of the neural network. In our case, thousands of song samples are input along with their expected genre target. The neural network performs computations on this data, to then be able to predict its next music sample once trained.
For now, I will not go into further detail to serve two purposes. One, to save you from a headache. Two, to demonstrate the learning of my experience creating a neural network for this project. In the next blog post, expect a more detailed rundown of the process of creating the neural network for this genre classification project. Our capstone project group has submitted our design draft. There has not been, yet any prototyping done yet, so stay tuned.