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

The video tutorial covers the process of converting sequences into input-target pairs using a map function. It explains how to prepare and shuffle the dataset, define batch size, and set buffer size. The tutorial also discusses setting embedding dimensions and defining model specifics for a recurrent neural network using LSTM or GRU. It then guides through defining and compiling the model using TensorFlow, setting a loss function, and choosing an optimizer like Adam. The video concludes with a brief on the next steps, including setting checkpoints and training the model.

What is the purpose of the output layer in the defined model?

Describe the loss function used in the model compilation.

What optimizer is used in the model compilation process?

What will be the next steps after compiling the model as mentioned in the video?