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Prediction Model

<p class="font_8">Task under Dept. of Information Technology, CHEARS</p>
<ul class="font_8">
<li><p class="font_8">Time limit for Video - Maximum 5 Minutes</p></li>
<li><p class="font_8">No. of maximum slides in presentations (if any): 15</p></li>

Dear Intern, You need to complete following task within the duration of 1 Month.

  1. Please follow the instructions given below on Prediction Mode.

  2. Prepare the PowerPoint presentation of your code explaining its functionality. (Optional)

  3. Record the video of code file with output, yourself explaining the steps.

  4. Submit the video and presentation / Code file (Link will appear on your profile in last week of your internship)

  5. Your video will be uploaded by our official account on the preferred social media of yours ( LinkedIn / Facebook / Instagram ). You will be tagged and the response of your connection and real world people on your presentation will be analyzed. This step is required to get the wide range feedback in real world. It is responsibility of the intern to divert the connection and advice them to put the feedback on your submission.

  6. Evaluation grades - 40 points ( Way of presentation ) ; 40 points ( Quality of work ) ; 20 points ( Social Response ) . Grade will appear on your certificate.

  7. Highest score holder will be declared as Intern of Month (In each domain IT / Public Health/ Public Relations).


Prediction Model:

  • Perform EDA on given data. Dataset Link

  • Create model Linear/Logistic/Decision Tree whatever you feel is best for the dataset given to you.

  • Clean code is a must.

About Dataset :

Each row represents a customer; each column contains customer’s attributes. The datasets have the following attributes or features:

  • State: string

  • Account length: integer

  • Area code: integer

  • International plan: string

  • Voice mail plan: string

  • Number vmail messages: integer

  • Total day minutes: double

  • Total day calls: integer

  • Total day charge: double

  • Total eve minutes: double

  • Total eve calls: integer

  • Total eve charge: double

  • Total night minutes: double

  • Total night calls: integer

  • Total night charge: double

  • Total intl minutes: double

  • Total intl calls: integer

  • Total intl charge: double

  • Customer service calls: integer

  • Churn: string

The "churn-bigml-20" dataset contains 667 rows (customers) and 20 columns (features).

The "Churn" column is the target to predict.


First slide should have following format :


<Your Name>

CHEARS Internship

Department of Information Technology

<Month> <Year>

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