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MangeshAgnihotri-4896 asked GiftA-MSFT commented

Help for Azure ML Studio experiment mapping

I am learning Azure ML (Studio) and please help me for below scenarios,
I have a bank customer data having column labelled as customer age, family members (1,2,3 &4), credit card (Yes /no) Personal Loan (Yes /no), education (1. Undergrad 2. Graduate 3. Advanced/professional).

  1. How to filter age column and find number of customers less than 45 years in % of total number of customers?

  2. Also need % customers who are having credit card as well Personal loan?

  3. which education category of customers are more prone to subscribe to personal loan?

  4. How to do visual analysis?

  5. How to calculate correlation between 2 columns?

Thanks in advance for your guidance. and incase tag to wrong group please guide to appropriate group

azure-machine-learning
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1 Answer

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GiftA-MSFT answered GiftA-MSFT commented

Hi, thanks for reaching out. I am assuming you are using Azure ML Studio Designer to work on this scenario. Please review response below:


  1. How to filter age column and find number of customers less than 45 years in % of total number of customers? As part of your data preparations step, you can use available data transformation modules such as apply sql transformation and apply math operation to perform data transformations.

  2. Also need % customers who are having credit card as well Personal loan? Similar to 1 above.

  3. Which education category of customers are more prone to subscribe to personal loan? This seems to be a multi-classification problem where you'd want to predict several categories. AML Studio has the following modules and algorithms for predicting classes. For future reference, this document helps you identify which algorithm to select based on the ML scenario.

  4. How to do visual analysis? With Azure ML Designer, you can Right Click on a module and select Visualize to visualize dataset output or results.

  5. How to calculate correlation between 2 columns? You can use Filter Based Feature Selection to identify the columns in your input dataset that have the greatest predictive power. The module includes correlation methods such as Pearson correlation and Chi-Squared.


Also, here are some useful resources to help get you started:

  • Azure Machine Learning Documentation.

  • Sample tutorials are available in Designer (newer drag and drop interface. Click Designer, select More Samples) and Classic (older drag and drop interface, via Azure AI Gallery, although some modules may not be available in designer, but a great starting point as well).

Hope this helps!







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Thanks GiftA-MSFT

I am not good in SQL and will try other way you suggested.
Thanks Again


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GiftA-MSFT avatar image GiftA-MSFT MangeshAgnihotri-4896 ·

Glad to be of help! If you are comfortable with python or R, you can use Execute Python Script or Execute R Script in Designer for data pre-processing as well. Furthermore, the python SDK is also available, so you can leverage Jupyter Notebook and Python SDK for your Data Science workflow. Here's a great resource for ML basics in python.



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