Preface¶

Repository Setup¶

This repository provides an end-to-end template for AI Singapore's AI engineers to onboard their AI projects. Instructions for generating this template is detailed in the cookiecutter template's repository's README.md.

While this repository provides users with a set of boilerplates, here you are also presented with a linear guide on how to use them. The boilerplates are rendered and customised when you generated this repository using cookiecutter.

Since we will be making use of this repository in multiple environments, ensure that this repository is pushed to a remote. Most probably you will be resorting to AI Singapore's GitLab instance as the remote. Refer to here on creating a blank remote repository (or project in GitLab's term). After creating the remote repository, retrieve the remote URL and push the local repository to remote:

$ git init
$ git remote add origin <REMOTE_URL>
$ git add .
$ git config user.email "<YOUR_AISG_EMAIL>"
$ git config user.name "<YOUR_NAME>"
$ git commit -m "Initial commit."
$ git push -u origin main

Go to this section for more information on interacting with the on-premise GitLab instance.

Guide's Problem Statement¶

For this guide, we will work towards building a neural network that is able to classify handwritten digits, widely known as the MNIST use-case. The model is then to be deployed through a REST API and used for batch inferencing as well. The raw dataset to be used is obtainable through a Google Cloud Storage bucket; instructions for downloading the data into your development environment are detailed under "Data Storage & Versioning", to be referred to later on.