Sales forecasting with Keras and Tensorflow

The contents will allow you to play with a Keras model forecasting sales for the data from: https://www.kaggle.com/c/rossmann-store-sales

You will be able to run your code locally and on google cloud platform for scalability.

Contents

• data: train and store coming from kaggle Rossman case:
  • train1, eval1: data filtered for just one store (date ascending)
• output - where the checkpoint models are stored
• gcp-output - where the checkpoint models from the cloud are downloaded
• notebooks - useful notebooks
• scripts - scripts (mainly gcloud) for dealing with google cloud
• trainer - main model

Setup

You will need:

• anaconda (https://conda.io/docs/user-guide/install/index.html)
• [optional] google cloud ml-engine (there's free tier available) and shell (https://cloud.google.com/sdk/)

Once you get those installed (and have this git repo cloned locally), run:

conda create -n mlengine python=2.7 anaconda

source activate mlengine

pip install -r requirements.txt

Note : (you can also set it up with python=3.6, but you might have problems running this on GCP ML-engine) Note2 : check the setup.txt with some dumps of the environment correctly setup.

Running locally

Use run_next_local.py, which will create a new job_name (with sequential numbers)

Running on GCP ML-engine

Use scripts under scripts