You will get I will build a customer churn prediction model using Python
Project details
Reduce customer churn and increase retention with predictive models in Python.
I will help you build a machine learning model to predict customer churn and identify high-risk customers before they leave.
This service includes:
✔️ Data cleaning and preprocessing
✔️ Feature engineering
✔️ Model training (Logistic Regression, Random Forest, XGBoost)
✔️ Performance evaluation (Accuracy, ROC-AUC, Precision/Recall)
✔️ Clear explanation of results
You will receive clean, well-documented Python code and a structured analysis.
• This solution helps businesses:
• Reduce churn
• Improve customer retention strategies
• Identify key churn drivers
Let’s turn your data into actionable insights.
I will help you build a machine learning model to predict customer churn and identify high-risk customers before they leave.
This service includes:
✔️ Data cleaning and preprocessing
✔️ Feature engineering
✔️ Model training (Logistic Regression, Random Forest, XGBoost)
✔️ Performance evaluation (Accuracy, ROC-AUC, Precision/Recall)
✔️ Clear explanation of results
You will receive clean, well-documented Python code and a structured analysis.
• This solution helps businesses:
• Reduce churn
• Improve customer retention strategies
• Identify key churn drivers
Let’s turn your data into actionable insights.
Data Tool
scikit-learnWhat's included
| Service Tiers |
Starter
$50
|
Standard
$120
|
Advanced
$220
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 3 | Unlimited |
Number of Graphs/Charts | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Model Variations | 1 | 3 | 4 |
Model Documentation | |||
Data Source Connectivity | - | - | |
Model Validation/Testing | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$70 - $250
Additional Revision
+$10Frequently asked questions
About Christian Junior
Machine Learning Engineer|Predictive Modeling & Data Analysis (Python)
Yaounde, Cameroon - 4:23 am local time
Are you looking to turn your data into accurate predictions and actionable insights?
I am a Machine Learning Engineer specialized in predictive modeling and data-driven solutions. I help businesses:
✔️ Build classification and regression models
✔️ Predict customer churn and sales
✔️ Segment customers using clustering
✔️ Improve model accuracy and performance
✔️ Clean, analyze, and structure datasets
Recent Projects
- Telco Churn Prediction (Classification models, feature engineering, evaluation)
- Sales Forecasting using ML techniques
- Customer Segmentation with K-Means
- Deep learning experiments (CNN, RNN, NLP models)
Technical Stack
- Python (Pandas, NumPy, Scikit-learn, PyTorch)
- SQL (MySQL, PostgreSQL)
- Data visualization (Matplotlib, Seaborn, Power BI)
- Model evaluation & optimization
My Approach
- Clear understanding of business goals
- Structured data analysis
- Clean and reproducible code
- Clear interpretation of results
I focus on delivering practical, reliable, and well-documented solutions.
Let’s discuss your project.
Steps for completing your project
After purchasing the project, send requirements so Christian Junior can start the project.
Delivery time starts when Christian Junior receives requirements from you.
Christian Junior works on your project following the steps below.
Revisions may occur after the delivery date.
data preparation
Collect and clean the customer dataset Clearly define what churn means in the customer context (cancellation, inactivity, cessation of purchases). Perform preprocessing: handling missing values, encoding categorical variables, normalizing data.
Model design and training
Select the appropriate algorithms (logistic regression/random forest/gradient boosting/deep learning depending etc). Divide the data into training and test sets. Train the model and adjust. Evaluate performance(accuracy, recall, F1-score, ROC/AUC).