Databricks AML sample is confusing: need separate sample of individual use case

The GIHUB sample designed for multiple use-cases and some of the customers are getting confused and unable to follow exactly what are the specific cells they need to run for a specific scenario. Please review and ensure the notebook has clear steps for each scenario.

https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-use-databricks-as-compute-target.ipynb

currently this notebook has all these scenarios which is difficult to follow:

The notebook will show:

1. Running an arbitrary Databricks notebook that the customer has in Databricks workspace
2. Running an arbitrary Python script that the customer has in DBFS
3. Running an arbitrary Python script that is available on local computer (will upload to DBFS, and then run in Databricks)
4. Running a JAR job that the customer has in DBFS.
5. How to get run context in a Databricks interactive cluster

從 aml-pipelines-use-databricks-as-compute-target.ipynb 開始，檢視 issue 中列出的五個 Databricks 情境。追蹤每個情境所需的儲存格，然後讓每個使用案例都能被獨立理解；完成的標準是，客戶無需瀏覽不相關的範例，就能識別並依照某個情境的儲存格執行。

由索引模型根據 Issue 內容生成。