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
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: https://bweigel.github.io/pydata_bln_2018/