22,99 €
inkl. MwSt.
Versandfertig in 6-10 Tagen
11 °P sammeln
Andere Kunden interessierten sich auch für
![Machine Learning on Data Lake]( "Machine Learning on Data Lake")
Machine Learning on Data Lake32,99 €![Supervised Sequence Labelling with Recurrent Neural Networks]( "Supervised Sequence Labelling with Recurrent Neural Networks")
Supervised Sequence Labelling with Recurrent Neural Networks125,99 €![Quantum Neural Network]( "Quantum Neural Network")
Quantum Neural Network29,99 €![Hybrid Neural Network]( "Hybrid Neural Network")
Hybrid Neural Network29,99 €![Probabilistic Logic Network]( "Probabilistic Logic Network")
Probabilistic Logic Network22,99 €![Neural Modeling Fields]( "Neural Modeling Fields")
Neural Modeling Fields22,99 €![Instantaneously Trained Neural Networks]( "Instantaneously Trained Neural Networks")
Instantaneously Trained Neural Networks29,99 €
Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. A recurrent neural network (RNN) is a class of neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Recurrent neural networks must be approached differently from feedforward neural networks, both when analyzing their behavior and training them. Recurrent neural networks can also behave chaotically. Usually, dynamical systems theory is used to model and analyze them. While a feedforward network propagates data linearly from input to output, recurrent networks (RN) also propagate data from later processing stages to earlier stages.