Tensorflow Tutorial using Google Cloud Platform

Credit goes to Adam Geitgey who is the author of this tutorial. I made some edits.

Requirements

This tutorial will help you build a simple deep learning neural network model using Tensorflow with Python to predict earnings.
This tutorial shows you how to use the Google API kit to use Google's machine learning API to save a model to the cloud
Once a model has been saved to the cloud you can call a model in any program using a credentials.json file to connect to the Google ML Api

Name		Name	Last commit message	Last commit date
Latest commit History 7 Commits
exported_model		exported_model
logs		logs
addition.py		addition.py
call_cloud_service.py		call_cloud_service.py
custom_visualization.py		custom_visualization.py
export_model_for_cloud.py		export_model_for_cloud.py
load_checkpoint.py		load_checkpoint.py
load_data.py		load_data.py
model.py		model.py
model_checkpoints.py		model_checkpoints.py
model_logging.py		model_logging.py
readme.md		readme.md
sales_data_test.csv		sales_data_test.csv
sales_data_training.csv		sales_data_training.csv
sample_input_prescaled.json		sample_input_prescaled.json
train_model.py		train_model.py
training.py		training.py
training_loop.py		training_loop.py
visualize_training.py		visualize_training.py