Neural Network Applications: Audio Processing: Wolfram U

Learn to process audio files using artificial intelligence and the neural network capabilities of Wolfram Language. The class covers data features, the need for a dedicated encoder, use of convolutional and recurrent neural networks. Build an audio classifier, adapt a predefined network, and extract and analyze data.

Summary
This course introduces neural network applications for audio processing. Learn about specific features of audio data and the need for a dedicated encoder. See examples of convolutional and recurrent neural networks. Get a glimpse of the fundamental building blocks of a neural network and their significance. You'll learn how to access neural network models from the Wolfram Neural Net Repository, build an audio classifier from scratch and understand the concept of "network surgery" for adapting a pre-defined network to use for audio analysis as well as for extracting data from a network for analysis and gaining insights. Finally, the technique of transfer learning is demonstrated for approaching complex problems.
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