So, we know what regression models are: take a dataset and create a model that will accurately predict the location of new points added to the dataset. Simple.
But, what if we had a dataset that looked like this?
you might be thinking…. this doesn’t look like the normal regression models or the graphs that I’ve seen before. In fact, it looks as if these two clusters are grouped in separate categories. And why is blue labeled 0 and orange labeled 1?
I’ll tell you now, this isn’t regression at all. You are correct when you assumed that the points are clustered into two groups. So is there a way to create a model that will accurate cluster new points in the right regression? …
Note, this article focuses more behind the mathematics of linear regression. You will need to understand the basics of partial derivatives and some linear algebra. If you are not too comfortable with these topics, bookmark this article, watch some Khan Academy videos and then have a read. You’ll thank me later.
Have you ever felt like you never properly understood gradient descent, regression or loss functions? Did you brush these concepts aside and focus all on the coding? Yeah, me too.
To understand what’s going on behind the algorithms, we must consider the math. I’ll be honest; machine learning mathematics is difficult. However, once we break down each concept and take a step-by-step approach, it will feel like a new world of understanding just emerged! …
Don’t you hate it when your clothes become smelly?
What if you had a shirt that would never trap odour, so that you are smelling like fresh laundry every time you wear it?
hmm… that would be pretty cool. But that’s impossible. You’re crazy.
Ouch. That hurt. Well… don’t hear it from me. Hear it from the scientists.
They are experimenting with nanotechnology — really small devices that communicate with really small objects in the nanoworld (atoms & molecules) — that has the ability to manipulate atoms and molecules and keep your shirt smelling like the fresh spring breeze. …