aws-mlops 0.0.4

AWS MLOps Python package

AWS MLOps package is implemented to help you like a framework for deploying what it is necessary for your best model.

The goal is to implement this package to keep your focus on your prep and test code using the AWS SageMaker services.

It is part of the educational repositories to learn how to write stardard code and common uses of the TDD and CI / CD.

Prerequisites

You can use Serverless framework for deploying the AWS services: if you want to use the guide below, you have to install Serverless framework before

npm install -g serverless

If you want to use another AWS tool, you can see the repository aws-tool-comparison before to implement your version.

Installation

The package is not self-consistent. So you have to download the package by github and to install the requirements before to deploy on AWS:

git clone https://github.com/bilardi/aws-mlops
cd aws-mlops/
pip3 install --upgrade -r requirements.txt
npm install
export AWS_PROFILE=your-account
export STAGE=development
SLS_DEBUG=* sls deploy --stage $STAGE
bash example/build_image.sh

Or if you want to use this package into your code, you can install by python3-pip:

pip3 install aws_mlops
python3
>>> import aws_mlops.mlops as MLOps
>>> help(MLOps)

Read the documentation on readthedocs for

• Usage

• Development

Change Log

See CHANGELOG.md for details.

License

This package is released under the MIT license. See LICENSE for details.