Time Series Analysis Services

A collection of services for time series analysis.

HTML User's Guide Hub

Getting Started

For more details on how to publish and test a service, select it from the list below:

Finance:

• cntk-next-day-trend (User's Guide) - This service uses a CNTK MLP to predict whether or not, for an input date, market will be above or below the previous day. [Reference]

Generic:

• cntk-lstm-forecast (User's Guide) - This service uses a CNTK LSTM model and Python SAX to extrapolate a given time series. [Reference]

• fbprophet-forecast (User's Guide) - This service uses Facebook's Prophet and Statsmodel to forecast points of a given time series. [Reference]

Contributing and Reporting Issues

Please read our guidelines before submitting an issue. If your issue is a bug, please use the bug template pre-populated here. For feature requests and queries you can use this template.

Authors

• Artur Gontijo - Maintainer - SingularityNET

Licenses

This project is licensed under the MIT License - see the LICENSE file for details.

Each service is licensed as followed:

• cntk-lstm-forecast - MIT License
• cntk-next-day-trend - MIT License