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 six certificates and degrees.

So this podcast episode is going to be a lot fluffier than the last.

I realize that the last episode was really heavy, really, really, really heavy mathematics

and algorithm stuff.

And I want to give you a break from that episode before we move on to logistic

regression. I may do this from time to time in between very technical episodes, try to punctuate

them with fluff. So you get a little bit of a breather. This episode I want to explore what are

the options for you as somebody pursuing machine learning, whether you want to get into the industry

professionally or you want to go down the deep rabbit hole as a scientist and crack the mysteries

of artificial intelligence and consciousness, or whether you're just doing this as a hobbyist

who's curious about the whole thing, working nights and weekends maybe just onside projects.

And one reason that I want to address this right now

is that in the previous episode, in the resources section,

...