AlgorithmiaSE

AlgorithmiaSE / OpenForecastPyTorch / 0.1.0

README.md

Overview

PyTorch is a python based library built to provide flexibility as a deep learning development platform. The workflow of PyTorch is as close as you can get to python’s scientific computing library – numpy.

Much like other frameworks, things like image recognition and timeseries sequences are a frequent use for PyTorch.

This particular model is using timeseries data to output a graph that can be viewed in your data bucket.

Applicable Scenarios and Problems

This model becomes an excellent demo on a few levels. The first one is that you can showcase how modules would be uploaded and added to create a PyTorch model here on the platform. You can talk through how a data scientist could create these modules outside and then push them to the platform as a way to deploy into production.

You can also showcase an option for data output on Algorithmia and showcase how the graph would dump out. Plus this is literally a demo of data for sales forecasting so it's a semi-business use case even if it is relatively simple.

Notes about this Demo

The graph output can be found in your data tab, shown in the photo below: