Gentle Introduction to Models for Sequence Prediction with RNNs
Last Updated on August 25, 2019
Sequence prediction is a problem that involves using historical sequence information to predict the next value or values in the sequence.
The sequence may be symbols like letters in a sentence or real values like those in a time series of prices. Sequence prediction may be easiest to understand in the context of time series forecasting as the problem is already generally understood.
In this post, you will discover the standard sequence prediction models that you can use to frame your own sequence prediction problems.
After reading this post, you will know:
- How sequence prediction problems are modeled with recurrent neural networks.
- The 4 standard sequence prediction models used by recurrent neural networks.
- The 2 most common misunderstandings made by beginners when applying sequence prediction models.
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Tutorial Overview
This tutorial is divided into 4 parts; they are:
- Sequence Prediction with Recurrent Neural Networks
- Models for Sequence Prediction
- Cardinality from Timesteps not Features
- Two Common Misunderstandings by Practitioners