ARTICLEMulti-step ahead forecasting with Application

Covers: theory of LSTM for Time Series
Estimated time needed: 30 minutes
Questions this item adddesses:
  • How to apply LSTMs for multi-step ahead time series forecasting?
How to use this item?

Read the article and run on your local machine

Author(s) / creator(s) / reference(s)
Jason Brownlee
Shortlist
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LSTM for Time Series Forecasting

Ozan OzyegenTotal time needed: ~3 hours
Learning Objectives
In this list you will learn about LSTM networks and apply it to simple time series forecasting problems
Potential Use Cases
Time Series Forecasting
Target Audience
INTERMEDIATEPeople familiar with other ML algorithms and Tensorflow
Go through the following annotated items in order:
ARTICLE 1. Understanding LSTM networks
  • Why do we need LSTM Networks?
  • How LSTM cells work?
  • What is the core idea behind LSTMs?
25 minutes
ARTICLE 2. LSTM cell implementation in PyTorch
  • How to implement LSTM equations in PyTorch?
30 minutes
ARTICLE 3. Univariate Time Series Forecasting Application
  • How to apply LSTMs for univariate time series forecasting?
30 minutes
ARTICLE 4. Multivariate Time Series Forecasting Application
  • How to apply LSTMs for multivariate time series forecasting?
30 minutes
ARTICLE 5. Multi-step ahead forecasting with Application
  • How to apply LSTMs for multi-step ahead time series forecasting?
30 minutes

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