Add `WeightsAndBiasesCallback` example

[nzw0301]

Motivation

Optuna introduces W&B integration, WeightsAndBiasesCallback to track optimisation since the next version update, v2.9.0. By following our convention, it would be great to provide an example code to use the callback functionality.

Description

The expected pull request contains

1. minimal example code like mlflow/keras_mlflow.py
2. README.md like mlflow/README.md;
3. Add weights and biases to README.md

Of course, weightsandbiases/requirement.txt and .github/workflows/weightsandbiases.yml are necessary.

Additional context (optional)

Add W&B's link from the main repository:

• https://github.com/optuna/optuna#integrations
• https://github.com/optuna/optuna/tree/master/examples

[xadrianzetx]

Will pick it up soon!

[nzw0301]

Oh, I realised that mlflow's example is not using MLflowCallback at all. It might not be a good example. Nevertheless, #55's example looks great. Thanks! @xadrianzetx

[xadrianzetx]

Yeah, I'll add callback example to mlflow after #55 😄

[nzw0301]

Amazing! I've just created issue #56 as a record.