Usman Attiq · imagine-talent

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GitHub

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Academic

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CGPA

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Year

2020

Education

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DOB

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Career

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Skills

Python, DASH, Plotly, Scikit-Learn, Bootstrap

Verbatim text

The exact text the LLM saw on the page (or the booklet text from the old import). This is what powers semantic search.

Customer Attrition Analytics 
 
 This project aims for predicting customer attrition in an effort to retain them. We worked on data 
 which included customers that have already churned (response) and their characteristics / 
 behaviour (predictors) before the customer turnover happened. By fitting a machine learning 
 model that relates the predictors to the response, we predicted the response for existing 
 customers. With the help of this project, an organization can analyse all relevant customer data and 
 develop focused customer retention programs for a good business. 
 Features Include: 
  Predicting whether customer will Churn or Not 
  Feature Importance Report: Calculating the factors affecting customer attrition and their 
 contribution  
  Extracting and Visualizing key information 
  Interactive Data Visualization to provide the user the freedom to perform the analysis on the data 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Technology Used: 
 Python, DASH, Plotly  
 Scikit-Learn, Bootstrap 
 Supervisor Name: 
 Dr. Hasan Mujtaba 
 Group Members:   
 Ayela Furrokh (i16 - 0030) 
 Usman Attiq (i16 - 0073) 
 Mirza Asad (i16 - 0136)

AI enrichment

Usman Attiq is a student who worked on a customer attrition analytics project using Python and machine learning to predict churn. The project involved feature importance analysis and interactive data visualization using Dash and Plotly.

Skills (AI)

["Python", "Machine Learning", "Scikit-Learn", "Dash", "Plotly", "Data Visualization", "Feature Importance Analysis"]

Status: ai_done

Provenance

Source file: Graduate Directory FAST School of Computing 2020 (Final Complete) (1).pdf
From job #23 page 191
Created: 1778170703