Python for Finance Cookbook

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In this section, we wanted to briefly mention some characteristics and extensions of the RNNs.

RNNs can be used for a variety of tasks. Here, we present the groups of models defined by the type of mapping they offer (together with an example of a use case):

• one to one: binary image classification
• one to many: creating a caption for an image
• many to one: classifying the sentiment of a sentence
• many to many: machine translation

Over the years, researches have come up with many new extensions/variants of the vanilla RNN model, each one overcoming some of the shortcomings of the original.

Bidirectional RNNs account for the fact that the time t output might not only depend on the past observations in the sequence, but also on ...