Friday 16:45–18:15 in Track 1

Deploying a machine learning model to the cloud using AWS Lambda

Dr. Benjamin Weigel

Audience level:


Take your machine learning model out of your desk drawer and show its benefit to the world through a simple API using AWS Lambda and API gateway. This tutorial will bridge the gap between having a machine learning model (e.g. in your Jupyter notebooks) and taking it to a level where others can benefit from it (i.e. through an API).


Agenda: - Why you need a service for your model? - Short intro to AWS Lambda and API gateway - Constructing a service around your model - Setting up AWS & deployment environment - Using the serverless framework to deploy your service to AWS - Things you should be aware of

Prerequisites: You should be familiar with using Docker and have it installed. Please refer to the GitHub repo accompanying this workshop and
install the necessary software: bweigel/ml_at_awslambda_pydatabln2018.

Also, you should already have an Amazon Web Services (AWS) account if you want to follow this session.

We will be using the free tier of AWS.

Slides for the talk:

Subscribe to Receive PyData Updates