Data and Tasks jar for Sequence Classification — Recurrent Neural Networks(RNNs)

In the last article, we touched upon the base of RNNs and discussed how RNNs inherently covers all the desired properties of an ideal network to address sequence-based problems

In this article, Data and Tasks jar (6 jars of Machine Learning) specific to Recurrent neural networks are discussed

Data and Tasks

RNNs are typically used for 3 types of tasks:

Sequence Classification:

• Here the complete sequence is ingested as the input
• And the “model produces one output at the end” for example say if the sequence conveys positive/negative sentiment or the video-based sequence represents a specific class (example: “Surya namaskar” pose)
• Here the “input sequence” might have “n tokens/words/video frames” but the “model produces one output”