You will get End to End Customer Churn Prediction Model with Streamlit
Project details
I developed a complete end-to-end machine learning system that predicts customer churn and helps businesses take proactive retention actions. The project goes beyond just model building—it covers the full lifecycle from data preprocessing to deployment-ready architecture, aligning closely with real-world business needs.
The model analyzes customer behavior patterns such as tenure, services, and billing to identify high-risk customers before they leave, enabling companies to reduce revenue loss and improve retention strategies. This is critical because churn directly impacts business growth and profitability, making predictive systems highly valuable in industries like telecom, SaaS, and banking.
🔥 What Sets Me (Dev) Apart
Self-Taught with Real-World Focus
I didn’t just learn theory—I built a production-style project that mirrors how real companies solve churn problems.
Business-Oriented Thinking
Instead of only focusing on accuracy, I focus on impact:
→ Which customers to target
→ How to reduce churn
→ What features drive decisions
End-to-End Ownership
From data cleaning → feature engineering → model building → evaluation → deployment mindset
(Not just a notebook project)
The model analyzes customer behavior patterns such as tenure, services, and billing to identify high-risk customers before they leave, enabling companies to reduce revenue loss and improve retention strategies. This is critical because churn directly impacts business growth and profitability, making predictive systems highly valuable in industries like telecom, SaaS, and banking.
🔥 What Sets Me (Dev) Apart
Self-Taught with Real-World Focus
I didn’t just learn theory—I built a production-style project that mirrors how real companies solve churn problems.
Business-Oriented Thinking
Instead of only focusing on accuracy, I focus on impact:
→ Which customers to target
→ How to reduce churn
→ What features drive decisions
End-to-End Ownership
From data cleaning → feature engineering → model building → evaluation → deployment mindset
(Not just a notebook project)
Machine Learning Tools
MLflow, NumPy, pandas, Python, Python Scikit-Learn, XGBoostWhat's included
| Service Tiers |
Starter
$80
|
Standard
$300
|
Advanced
$799
|
|---|---|---|---|
| Delivery Time | 4 days | 7 days | 12 days |
Number of Revisions | 2 | 3 | 5 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$149 - $999About Arham
Data Scientist and Ai for Business
Mumbai, India - 8:56 am local time
Steps for completing your project
After purchasing the project, send requirements so Arham can start the project.
Delivery time starts when Arham receives requirements from you.
Arham works on your project following the steps below.
Revisions may occur after the delivery date.
Getting information from client to start work
Explore and preprocess data for training