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. Welcome to the first episode of the exclusive podcast Machine Learning Applied,

a companion podcast to Machine Learning Guide,

and thank you for becoming a patron to unlock this series.

I very much appreciate it.

This series is going to be a much more applied approach to machine learning.

We're going to talk about degrees and certificates, interviewing tactics, tech tips and tricks,

stuff around pandas, numpy, tensor flow, maybe any sort of hot news that's going on the

machine learning community, all that stuff that fits into a traditional style podcast, where the

machine learning guide podcast is a little bit unusual in that they're very long one-hour episodes

that are educational and sequential. Machine learning guide is more what you'd get out of iTunes,

you, or the great courses, machine learning applied. This podcast is going to be like your traditional podcast.

In this episode, we're going to do a throwback to a machine learning guide podcast on

certificates and degrees, where we talked about Coursera specializations,

...