Data Science and Machine Learning (Theory and Projects) A to Z - Project I_ Book Writer: Modelling RNN Architecture

The video tutorial explains how to model sequence prediction problems using recurrent neural networks (RNNs), specifically focusing on many-to-many architectures. It discusses the setup of training data, where input and target sequences are of equal length, and demonstrates how to implement this in Python. The tutorial provides a step-by-step guide to preparing data, creating input-target pairs, and setting up the RNN model for character sequence prediction.

Describe the process of generating input sequences and their corresponding targets.

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How does the model predict the next character in a sequence?

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What are the implications of choosing different sequence lengths for training the model?

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What is the role of the helper function mentioned in the video?

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