In this workshop, we learned about a new class of neural networks. These are an excellent choice for working with data that comes in sequences of arbitrary length. This workshop was split into two consecutive weekly meetings.
Recurrent neural networks (RNNs) have important applications in language models and time series analysis.
RNNs have a lot in common with the Multilayer Perceptrons we've been learning about, but in summary, they can run a linear layer in a cycle with its inputs being affected by previous outputs to allow them to take in a sequence of arbitrary size and a defined order, such as words in a paragraph, or samples in an audio file.
In the first part of this workshop, members worked together to train a model that can classify an Amazon product review as either positive or negative -- having 1-2 stars, or 4-5 stars.
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