Time Series Forecasting

LSTM for Time Series Forecasting

  • Univariate LSTM Models : one observation time-series data, predict the next value in the sequence
  • Multivariate LSTM Models : two or more observation time-series data, predict the next value in the sequence
    • Multiple Input Series : two or more parallel input time series and an output time series that is dependent on the input time series
    • Multiple Parallel Series : multiple parallel time series and a value must be predicted for each
  • Univariate Multi-Step LSTM Models : one observation time-series data, predict the multi step value in the sequence prediction.
  • Multivariate Multi-Step LSTM Models : two or more observation time-series data, predict the multi step value in the sequence prediction.
    • Multiple Input Multi-Step Output.
    • Multiple Parallel Input and Multi-Step Output.

Machine Learning for Multivariate Input

Statistical Method for Multivariate Input

Machine Learning for Univariate Input

Statistical Method for Univariate Input

Jupyter Notebook Examples

Univariate ARIMA

import statsmodels

Univariate LSTM

import keras

Multivariate VAR

(Note: VAR should only for Stationary process - Wikipedia)

Multivariate LSTM

Prophet and Kats from Facebook

Note on Multivariate and Univariate

Software

Other Time Series

Precipitation Forecasting

Deep Learning for Forecasting

top open source deep learning for time series forecasting frameworks.

  1. Gluon This framework by Amazon remains one of the top DL based time series forecasting frameworks on GitHub. However, there are some down sides including lock-in to MXNet (a rather obscure architecture). The repository also doesn't seem to be quick at adding new research.
  2. Flow Forecast This is an upcoming PyTorch based deep learning for time series forecasting framework. The repository features a lot of recent models out of research conferences along with an easy to use deployment API. The repository is one of the few repos to have new models, coverage tests, and interpretability metrics.
  3. sktime dl This is another time series forecasting repository. Unfortunately it looks like particularly recent activity has diminished on it.
  4. PyTorch-TS Another framework, written in PyTorch, this repository focuses more on probabilistic models. The repository isn't that active (last commit was in November).

eBook Forecasting