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Learn when to use recurrent neural networks and why feed-forward networks can't be used for exact order of sequences in artificial intelligence. Wolfram Language examples shown.
Summary
Recurrent neural networks are useful when solving problems dealing with sequential data. Learn how you can work with recurrent neural nets using the neural network framework in Wolfram Language. See a simple example of integer addition and look at an advanced application of recurrent nets for question-answering tasks.
Featured Products & Technologies: Wolfram Language (available in Mathematica and Wolfram|One), Wolfram Neural Net Repository
You'll Learn To
Recognize when recurrent networks are useful
Implement a recurrent neural network
Work with built-in layers specifically intended for recurrent networks
Use the neural network framework in Wolfram Language
Summary
Recurrent neural networks are useful when solving problems dealing with sequential data. Learn how you can work with recurrent neural nets using the neural network framework in Wolfram Language. See a simple example of integer addition and look at an advanced application of recurrent nets for question-answering tasks.
Featured Products & Technologies: Wolfram Language (available in Mathematica and Wolfram|One), Wolfram Neural Net Repository
You'll Learn To
Recognize when recurrent networks are useful
Implement a recurrent neural network
Work with built-in layers specifically intended for recurrent networks
Use the neural network framework in Wolfram Language
