Welcome back to Machine Learning Guide. I'm your host, Tyler Rinelli.

MLG teaches the fundamentals of machine learning and artificial intelligence.

It covers intuition, models, math, languages, frameworks, and more.

Where your other machine learning resources provide the trees, I provide the forest.

Visual is the best primary learning modality, but audio is a great supplement during exercise commute and chores.

Consider MLG your syllabus with highly curated resources for each episode's details at OCdevel.com forward slash MLG.

I'm also starting a new podcast which could use your support. It's called

Lefnear's Life Hacks and teaches productivity focused tips and tricks, some which could prove

beneficial in your machine learning education journey. Find that at Ocdevel.com forward slash

LLH. This is episode five, linear regression.

In this episode, we're finally going to get into the nitty-gritty, your first machine

learning algorithm, linear regression.

Now, let's recall about machine learning that it's a very hierarchical field.

Starting at the top, something I call mathematical decision making.

I don't actually know what they call this super field.

Can be broken down into artificial intelligence, statistics, operations, research, control theory,

and some other fields.

Artificial intelligence is broken down into machine learning.

That's where we are.

And then ML is broken down into supervised learning, unsupervised learning, and reinforcement

learning. So we're going to go down the supervised learning rabbit hole. You'll find the supervised learning, unsupervised learning, and reinforcement learning.

So we're going to go down the supervised learning rabbit hole.

...