Short Description Built a machine learning solution to identify customers at risk of leaving and ...Short Description Built a machine learning solution to identify customers at risk of leaving and ...
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Lucy Brown
• 20h
Short Description
Built a machine learning solution to identify customers at risk of leaving and provide insights that can support customer retention strategies.
Description
I developed a machine learning solution for predicting customer churn.
The project involved analyzing customer behavior, preparing and cleaning the dataset, engineering relevant features, training multiple machine learning models, and evaluating their predictive performance.
The objective was to identify customers who are more likely to leave so that businesses can take proactive retention actions.
Technologies
Python · Pandas · NumPy · Scikit-learn · Machine Learning · Matplotlib · Seaborn
Key Deliverables
Data cleaning and preprocessing
Exploratory Data Analysis
Feature engineering
Customer behavior analysis
Machine learning model development
Model evaluation
Feature importance analysis
Prediction pipeline
Business recommendations
Results
The final solution provides a practical framework for:
Identifying high-risk customers
Understanding major churn factors
Supporting targeted retention campaigns
Using predictive analytics for business decisions
Data EngineeringData ModelingProduct Data AnalyticsMatplotlibPythonscikit-learn
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