Modified Dense layer documentation for use_bias with batch normalization

[Kayyuri]

Clarified the use of 'use_bias' in the Dense layer documentation to include information about batch normalization.

[gemini-code-assist]

Summary of Changes

Hello @Kayyuri, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request enhances the clarity of the Dense layer's documentation by explicitly addressing the use of the use_bias parameter in conjunction with batch_normalization. The update aims to help users understand when it is appropriate to disable the bias term in a Dense layer, thereby preventing redundant parameters and promoting more efficient model design when batch normalization is subsequently applied.

Highlights

• Documentation Update: The documentation for the Dense layer in Keras has been updated to provide clearer guidance on the use_bias parameter.
• Batch Normalization Interaction: A specific clarification has been added regarding the interaction between use_bias and batch_normalization, advising that use_bias can be set to False when batch_normalization is applied, as batch normalization includes its own parameters for handling shifts.

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[gemini-code-assist]

Code Review

This pull request aims to clarify the usage of the use_bias parameter in the Dense layer when it is followed by a BatchNormalization layer. The intention is good, but the added documentation has some grammatical errors and lacks clarity. I've provided a suggestion to improve the wording, making it more accurate and easier to understand, while also adhering to the documentation style.

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 82.56%. Comparing base (846a297) to head (89b5757).

Additional details and impacted files

@@           Coverage Diff           @@
##           master   #21888   +/-   ##
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  Coverage   82.56%   82.56%           
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  Files         578      578           
  Lines       59786    59786           
  Branches     9384     9384           
=======================================
  Hits        49365    49365           
  Misses       8001     8001           
  Partials     2420     2420           

Flag	Coverage Δ
keras	82.38% <ø> (ø)
keras-jax	62.89% <ø> (ø)
keras-numpy	57.45% <ø> (ø)
keras-openvino	34.33% <ø> (ø)
keras-tensorflow	64.42% <ø> (ø)
keras-torch	63.59% <ø> (ø)

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