docs: add aisample title genre text classification

[thinkall]

Related Issues/PRs

None

What changes are proposed in this pull request?

Add a title genre text classification notebook for aisample under notebooks/community/aisample.

How is this patch tested?

• I have written tests (not required for typo or doc fix) and confirmed the proposed feature/bug-fix/change works.

Does this PR change any dependencies?

• No. You can skip this section.
• Yes. Make sure the dependencies are resolved correctly, and list changes here.

Does this PR add a new feature? If so, have you added samples on website?

• No. You can skip this section.
• Yes. Make sure you have added samples following below steps.

1. Find the corresponding markdown file for your new feature in website/docs/documentation folder.
   Make sure you choose the correct class estimators/transformers and namespace.
2. Follow the pattern in markdown file and add another section for your new API, including pyspark, scala (and .NET potentially) samples.
3. Make sure the DocTable points to correct API link.
4. Navigate to website folder, and run yarn run start to make sure the website renders correctly.
5. Don't forget to add <!--pytest-codeblocks:cont--> before each python code blocks to enable auto-tests for python samples.
6. Make sure the WebsiteSamplesTests job pass in the pipeline.

AB#1935137

[github-actions]

Hey @thinkall 👋!
Thank you so much for contributing to our repository 🙌.
Someone from SynapseML Team will be reviewing this pull request soon.
We appreciate your patience and contributions 💯!

[mhamilton723]

Lovely work heres a few suggestions!

• No need for this line: raw_df.createOrReplaceTempView("raw_data")
• are these lines necessary for this CSV?

multiLine=True,
   quote='"',
   escape='"',

• We have a class balancer tool specifically to deal with label imbalence, this will add a weight thats proportional to the deficit https://microsoft.github.io/SynapseML/docs/next/documentation/estimators/estimators_core/#classbalancer

• We have text featurizer that might be able to make alot of these steps a single model call
  https://mmlspark.blob.core.windows.net/docs/0.10.0/pyspark/synapse.ml.featurize.text.html#module-synapse.ml.featurize.text.TextFeaturizer

• EvaluatorType -> use snake_case here and elsewhere

[thinkall]

Thanks @mhamilton723 for the feedbacks. They helped a lot :-)

Just TextFeaturizer is not applied. The output column only contains indexes of words, not the words. Thus we can't use the output df for plotting word cloud. Moreover, we want to apply word2vec for vectorization. It seems that TextFeaturizer doesn't support it.

[thinkall]

/azp run

[azure-pipelines]

Azure Pipelines successfully started running 1 pipeline(s).

[codecov-commenter]

Codecov Report

Merging #1617 (5c08d20) into master (0f54bc6) will decrease coverage by 0.05%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master    #1617      +/-   ##
==========================================
- Coverage   83.61%   83.56%   -0.06%     
==========================================
  Files         288      288              
  Lines       15334    15334              
  Branches      747      747              
==========================================
- Hits        12822    12814       -8     
- Misses       2512     2520       +8     

Impacted Files	Coverage Δ
.../azure/synapse/ml/param/PythonWrappableParam.scala	66.66% <0.00%> (-8.34%)	⬇️
...ft/azure/synapse/ml/param/JsonEncodableParam.scala	57.14% <0.00%> (-7.15%)	⬇️
...re/src/main/python/synapse/ml/core/schema/Utils.py	67.10% <0.00%> (-5.27%)	⬇️
.../execution/streaming/continuous/HTTPSourceV2.scala	92.08% <0.00%> (-0.72%)	⬇️
...ft/azure/synapse/ml/cognitive/ComputerVision.scala	73.10% <0.00%> (+1.26%)	⬆️
...osoft/azure/synapse/ml/core/utils/AsyncUtils.scala	80.00% <0.00%> (+5.00%)	⬆️

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[mhamilton723]

/azp run

[azure-pipelines]

Azure Pipelines successfully started running 1 pipeline(s).