JuPyter Notebooks and Python Package for Deep Learning Model Exploration, Translation and Deployment
This repository contains the sourcecode related to my blogpost series on Medium on deep learning model exploration, translation and deployment using the EMNIST dataset.
conda
, just create a new environment from env.yml
with conda env create -f env.yml
. This will create the environment emnist_dl
.conda activate emnist_dl
python setup.py install
notebooks/
I provide six JuPyter notebooks to guide through the code. I advise you to set everything up, read each blogpost and go trough the referenced notebooks to try things out yourself.
4_production_TFServing.ipynb
5_production_Webserver.ipynb
6_conclusion_Serving_Performance_Comparison.ipynb
The code has been tested with Docker Version 18.06.1-ce-mac73 (26764)
This project has been set up using PyScaffold 3.1rc2. For details and usage information on PyScaffold see https://pyscaffold.org/.