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 18, natural language processing, part one.

In this episode, I'm going to talk about a subfield of machine learning called

Natural Language Processing, NLP.

NLP is a subfield of machine learning, and it is quite the rabbit hole. I'm going to take you on an

adventure away from machine learning proper, a specialization within machine learning. This is going

to be a three-part series. This first episode I'm going to be describing the general topics in

NLP. In the next episode, I'll talk about the shallow learning and traditional

approaches to NLP. And in the third episode, I'll talk about recurrent neural networks and

word to VEC, that is the deep learning approach, state of the art in NLP. NLP is a microcosm

of machine learning proper. It's its own world of machine learning algorithms.

NLP uses maybe half traditional machine learning algorithms and then half of its own algorithms

dedicated to its own field. So that's what I mean that I'm going to be taking you on a rabbit hole

...