AWS-foryou helps you decide which AWS instance to use for your machine learning project. Input your algorithm, dataset, and your choice of constraints, be it time or budget, and AWS-foryou will help you decide which instance best suits your needs.

AWS-foryou/
  |- README.md
  |- awsforyou/
    |- __init__.py
    |- algo_runner.py
    |- aws_metadata.py
    |- aws_pricing.py
    |- benchmark_runner.py
    |- recommender.py
    |- report_generator.py
    |- total_time_component.py
    | - ui/
      | - template.html
    |- tests/
      |- __init__.py
      |- test_algo_runner.py
      |- test_aws_metadata.py
      |- test_aws_pricing.py
      |- test_benchmark_runner.py
      |- test_keras_mnist.py
      |- test_reccomender.py
      |- test_report_generator.py
      |- test_total_time_compoment.py
  |- data/
    |- aws-scorecard.csv
  |- docs/
    |- component-specification.md
    |- functional-specification.md
  |-examples/
    |-demo,py
    |-examples.ipynb
    |-sklearn_diabetes.py
    |-x_diabetes.csv
    |-y_diabetes.csv
  |- setup.py
  |- requirements.txt
  |- LICENSE

Clone the repo and create a virtual environment in the root of the repo

python -m venv venv
source venv/bin/activate

If you're using Anaconda, create and activate a new conda environment. For conda run

conda create --name awsforyou
conda activate awsforyou

Install the dependencies from the requirements.txt file using

python -m pip install -r requirements.txt

If you don't have setuptools and wheel install them using

python -m pip install --upgrade setuptools wheel

Install the package using the following command

python setup.py sdist bdist_wheel

This will generate the pip installation package awsforyou-0.0.1-py3-none-any.whl in the dist/ directory. The package awsforyou can now be installed using

pip install awsforyou-0.0.1-py3-none-any.whl

To see how to use the package to get instance recommendation, refer to the example notebook

Below is an image of how the output of our recommendation looks like.