An Introduction to Recurrent Neural Networks and the Math That Powers Them
When it comes to sequential or time series data, traditional feedforward networks cannot be used for learning and prediction. A mechanism is required to retain past or historical information to forecast future values. Recurrent neural networks, or RNNs for short, are a variant of the conventional feedforward artificial neural networks that can deal with sequential data and can be trained to hold knowledge about the past.
After completing this tutorial, you will know:
- Recurrent neural networks
- What is meant by unfolding an RNN
- How weights are updated in an RNN
- Various RNN architectures
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