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.

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

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

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