This is a extra mark Supervised Learning assignment - the last few assignments I have had done have come back missing items and short cuts were taken which cost me some marks - I currently have 2...

This is a extra mark Supervised Learning assignment - the last few assignments I have had done have come back missing items and short cuts were taken which cost me some marks - I currently have 2 assignments on the go that is why I need help please follow the Rubric and protocols and show the code not just the answers thank you ..

Background and Context

Best insurance company and My Bank have set up a Bancassurance(Bancassuranceis a relationship between abankand aninsurancecompany), now using the data ofliability customers of My Bank, The Best insurance company wants to convert customers with both a life insurance policy and an account in My bank to loan customers(taking a loan against a life insurance policy)

A campaign that the company ran last year for liability customers showed a healthy conversion rate of over 12.56% success. You are provided with data of customers who have an account in My bank and life insurance policy in the Best insurance company

You as a data scientist at the Best insurance company have to build a model to identify the positively responding customers who have a higher probability of purchasing the insurance. This will increase the success ratio and reduce the cost of the campaign.

Objective

• To predict whether a liability customer will buy a loan or not.


• Which variables are most significant for making predictions.


• Which segment of customers should be targeted more.

Data Dictionary
* CUST_ID: Unique Customer ID
* Target: Field - 1: Responder, 0: Non-Responder
* Age: Customer Age in years
* Gender: Male / Female / Other
* Balance: Monthly Average Balance
* Occupation: Professional / Salaried / Self Employed / SelfEmployed Non-Professional.
* SCR: Marketing Score
* HOLDING_PERIOD: Duration in days to hold the money
* ACC_TYPE: Account Type: Current Account / Saving Account
* ACC_OP_DATE: Account Open Date
* LEN_OF_RLTN_IN_MNTH: Length of Relationship in Months
* NO_OF_L_CR_TXNS: Number of Credit Transactions
* NO_OF_BR_CSH_WDL_DR_TXNS: Branch Cash Withdrawal Debit Transactions
* NO_OF_ATM_DR_TXNS: Number of ATM Debit Transactions
* NO_OF_NET_DR_TXNS: Number of Net Banking Debit Transactions
* NO_OF_MOB_DR_TXNS: Number of Mobile Banking Debit Transactions
* NO_OF_CHQ_DR_TXNS: Number of Cheque Debit Transactions
* FLG_HAS_CC: Has Credit Card - 1: Yes, 0: No
* AMT_ATM_DR: Amount Withdrawn from ATM
* AMT_BR_CSH_WDL_DR: Amount cash withdrawn from Branch
* AMT_CHQ_DR: Amount debited by Cheque Transactions
* AMT_NET_DR: Amount debited by Net Transactions
* AMT_MOB_DR: Amount debited by Mobile Transactions
* FLG_HAS_ANY_CHGS: Flag: Has any banking charges
* FLG_HAS_NOMINEE: Flag: Has Nominee - 1: Yes, 0: No
* FLG_HAS_OLD_LOAN: Flag: Has any earlier loan - 1: Yes, 0: No

Best Practices for Notebook :

• The notebook should be well-documented, with inline comments explaining the functionality of code and markdown cells containing comments on the observations and insights.


• The notebook should be run from start to finish in a sequential manner before submission.


• It is preferable to remove all warnings and errors before submission.


• The notebook should be submitted as an HTML file (.html) and NOT as a notebook file (.ipynb)
  
  

Best Practices for Presentation :

Like in real-world projects, the ultimate destination of any project or work is generally an executive or decision-making meeting, where you are supposed to present your solution to the business problem, based on the project/work you have done. The purpose of this presentation is to simulate that kind of experience and to draw the attention of your audience (a business leader like CMO, COO, CFO, or CEO) to the key points of your project, which are

• Business Overview of the problem and solution approach


• Key findings and insights which can drive business decisions


• Model overview and performance summary


• Business recommendations

Please keep the following points in mind while making the presentation:

• Focus on explaining the takeaways in an easy-to-understand manner.


• The inclusion of the potential benefits of implementing the solution will give you the edge.


• Copying and pasting from the notebook is not a good idea, and it is better to avoid showing codes unless they are the focal point of your presentation.


• Please submit the presentation in PDF format only.

Submission Guidelines :

1. There are two parts to the submission:
   
   
   1. A well commented Jupyter notebook [format - .html]
   
   
   2. A presentation as you would present to the top management/business leaders [format - .pdf ](you have to export/save the .pptx file as .pdf)
   
   
   
   


2. Any assignment found copied/ plagiarized with other groups will not be graded and awarded zero marks


3. Please ensure timely submission as any submission post-deadlinewill not be accepted for evaluation


4. Submission will not be evaluated if,
   
   
   1. it is submitted post-deadline, or,
   
   
   2. more than 2 files are submitted
   
   
   
   

Happy Learning!!