Serverless ML

Travis chat

Towards Data Science

Wrangling data and training models can feel a little… disconnected. In this post I’ll walk through deploying an ML model in the cloud. It’s quick, easy and free (I think).

🦾 Serverless ML Execution

TheSequence

📝 Editorial One of the most challenging aspects of modern ML solutions is to match the right infrastructure for executing a given ML model. Some are executed continuously, while others intermittently...

Serverless ML: Deploying Lightweight Models at Scale

Towards Data Science

Deploying machine learning (ML) models into production can sometimes be something of a stumbling block for Data Science (DS) teams. A common mode of deployment is to find somewhere to host your…

The Road to a Serverless ML Pipeline in Production — Part II

Towards Data Science

In part 1, I explained the process we went through in creating a fully-automated MLOps architecture. In this post, I'll show you the solution we ended up, including code examples of how to implement t...

The Road to a Serverless ML Pipeline in Production — Part I

Towards Data Science

How we managed to run different types of models (our own Python models), each of which with several live versions in production - all in a serverless environment

SageMaker Serverless Inference Is Now Generally Available

Towards Data Science

Exploring The Latest SageMaker Inference Option Continue reading on Towards Data Science

Serverless

Full Stack Python

Serverless is an deployment architecture where servers are not explicitly provisioned and code is run based on pre-defined events.

The Serverless Framework — Streamlined

Level Up Coding

How I’ve eliminated the pain points I’ve had over the years with the Serverless Framework for my Typescript applications deployed on AWS.

A Brief Introduction to Serverless Computing

Towards Data Science

Over the last decade or two, cloud computing has come to dominate many of the skills and processes needed to develop ‘modern’ software. This is increasingly true for adjacent fields too, including…

The Myths and Misconceptions About Serverless

Better Programming

The demand for serverless computing solutions is growing. But before we go any further, let’s try to explain what this relatively new phenomenon is. The name serverless is pretty contradictory. No…

Serverless Deployment of Machine Learning Models on AWS Lambda

Towards Data Science

In my previous guide, we explored the concepts and methods in deploying machine learning model on AWS Elastic Beanstalk. Despite being largely automated, services like AWS Elastic Beanstalk still…

Models as Serverless Functions

Towards Data Science

I recently published Chapter 3 of my book-in-progress on leanpub. The goal with this chapter is to empower data scientists to leverage managed services to deploy models to production and own more of…