Update the documentation with the latest changes in parameter differentiability

[dime10]

Context: This PR updates various points in the documentation regarding which data types can be differentiated in autograd, and what the defaults for parameter trainability are.

Description of the Change:

Benefits:

Possible Drawbacks:

Related GitHub Issues:

[github-actions]

Hello. You may have forgotten to update the changelog!
Please edit doc/releases/changelog-dev.md with:

• A one-to-two sentence description of the change. You may include a small working example for new features.
• A link back to this PR.
• Your name (or GitHub username) in the contributors section.

[codecov]

Codecov Report

Merging #2125 (f9ef1a1) into master (fec189f) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master    #2125   +/-   ##
=======================================
  Coverage   99.19%   99.19%           
=======================================
  Files         228      228           
  Lines       17472    17472           
=======================================
  Hits        17331    17331           
  Misses        141      141           

Impacted Files	Coverage Δ
pennylane/_grad.py	100.00% <ø> (ø)
pennylane/qnn/keras.py	100.00% <ø> (ø)
pennylane/qnn/torch.py	100.00% <ø> (ø)
pennylane/qnode.py	100.00% <ø> (ø)

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[josh146]

Thanks @dime10! Don't forget to also update the changelog (you can probably just list this PR under the changelog entry for the just-merged requires_grad=False PR)