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. You're listening to Machine Learning Applied, and in this episode we're going to talk about

machine learning hosting solutions out there with a special emphasis on serverless technology.

In the last machine learning applied episode, we talked about various tech stack solutions,

especially for serverless solutions for hosting your server.

The Amplify stack in particular uses behind the hood AWS Lambda.

And AWS Lambda is a very popular solution for serverless architectures.

AWS Lambda lets you write a single code function, whether it's Node.js or Python,

and then that function in conjunction with AWS API Gateway, will be exposed as a rest endpoint that your client can

call. Very powerful and saves you a lot of time and heartache. Now, we want to achieve this

level of functionality when deploying our machine learning models. So in this episode,

when I'm talking about machine learning deployment solutions, I want to push towards as much

of a serverless solution for deploying your machine learning models as possible. Now, I want to

preface by saying my own experience in machine learning hosting is slightly unlimited and in my experience trying to find

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