💡 [REQUEST] - Making the tutorial more coherent

🚀 Describe the improvement or the new tutorial

The 3-series tutorial set (linked in existing tutorial set) is disconnected in term of concepts being introduced and reused; like the

• "Dataset" which is introduced in first tutorial but is not leveraged in next;
• Intricate details like explanation of use of torch.LongTensor is skipped in part 2 (generating)

I wish to modify the tutorials content by:

• adding a linear flow of concepts and then updating the code in follow up concepts such that the end-user is aware of what is different from last time.
• Add details in explanation of what we are doing and why
• Add pictures that reinforce what is we are doing and how is it related to big picture we wish to do.

Existing tutorials on this topic

Tutorials with the issue

• https://pytorch.org/tutorials/intermediate/char_rnn_classification_tutorial.html
• https://pytorch.org/tutorials/intermediate/char_rnn_generation_tutorial.html
• https://pytorch.org/tutorials/intermediate/seq2seq_translation_tutorial.html

Additional context

Hey,
I love tech-writing and wish to make tech adoption easier for all.

Bit of my works you can find.

• https://github.com/LunaticMaestro/Content-Based-Book-Recommender
• I am author of the AI Core tutorials (m ex-SAP employee): https://developers.sap.com/group.ai-core-get-started-basics.html

Compare the three linked tutorials: char_rnn_classification_tutorial.html, char_rnn_generation_tutorial.html, and seq2seq_translation_tutorial.html. Trace which concepts are introduced and reused, including Dataset and torch.LongTensor, then define a coherent progression with explanatory text and pictures. Done means the tutorial set clearly connects each follow-up concept to the previous one.