Advanced Chatbots with Deep Learning and Python - Encoding

The video tutorial covers setting up placeholders for input and question sequences, followed by building three encoders: Encoder M, Encoder C, and a Question Encoder. Each encoder is constructed using a sequential model with embedding and dropout layers. The tutorial explains how to integrate input sequences into these encoders and prepares for the next steps involving activation functions.

What steps are involved in creating the input encoder M?

What will be the output dimension for the embedding layer in encoder C?

How does the question encoder differ from the other encoders mentioned?