Machine Learning api template

This project implements the deployment of a functional Machine Learning.

1 Software Need/Solution

Need: a Machine Learning template to better organize and deploy a Machine Learning model.

Solution: My software is a suggestion on how to organize a Machine Learning experiment, with the capabilities of train a Machine Learning Model. It also includes CI/CD on how to deploy training to AWS SageMaker.

2 Prerequisites

This software does not requires specific hardwares. This project is based on Python 3.8, pipenv, Makefile, and Docker.

3 Build

3.1 Locally

I provide the followin Makefile target commands:

• make data - download the training data,
• make train - train the machine learning model with the data and sabe the Machine Learning artifact,

4 How do I install it?

This is a service software, the idea is to use its final result an API. If you intend to develop I provide detailed package requirements in the requirements.txt file or Pipfile and Pipfile.lock for pipenv. Also Makefile target make install will install requirements using pipenv and docker.

5 Is the software ready?

5.1 Hello World

5.2 Hello Mars

6 Tips and Tricks

% code samples

% config tips

7 Troubleshooting

% FAQs

% Bugs

8 Contributions

% Community

% Explain How

9 Licensing and Credits

The repo provides the capability of training and serving a sklearn model capable of predicting divorce according to several features available for the "Divorce Predictors data set Data Set" dataset publicly available here.

10 List of Changes

11 Proof of functionality

After succesfully applying the deployment at EKS I obtained the following terminal screen: