You will get a credit default prediction model using Python and ML
Project details
I will build a credit default prediction model using your dataset and Python. You’ll receive a clean and structured dataset, visual EDA, trained ML models (e.g. Logistic Regression, XGBoost), and a final PDF report with key insights and model performance. My focus is clarity, quality, and making risk assessment actionable for your business.
Machine Learning Tools
Azure Machine Learning, BigDL, GitHub Copilot, NumPy, pandas, Python, Python Scikit-Learn, scikit-learn, TensorFlow, XGBoostWhat's included
| Service Tiers |
Starter
$60
|
Standard
$120
|
Advanced
$180
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 0 | 1 | 2 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 4 | 6 | 8 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$25 - $40
Additional Revision
+$15
Additional Model Variation
(+ 1 Day)
+$25
Additional Scenario
(+ 1 Day)
+$10
Additional Graph/Chart
(+ 1 Day)
+$10Frequently asked questions
1 review
(1)
(0)
(0)
(0)
(0)
This project doesn't have any reviews.
YI
Yousef I.
Dec 18, 2025
Data visualisation
About Shynggys
I turn complex data into insights and predictions using Python
Astana, Kazakhstan - 5:46 am local time
I help teams and organizations clean, explore, and model their data using a structured, result-oriented approach — combining technical tools with real-world logic.
⚙️ My skills include:
• Python (pandas, scikit-learn, matplotlib, statsmodels)
• Machine Learning (classification, regression, forecasting, NLP)
• Data Cleaning, Feature Engineering, EDA
• Dashboards in Power BI, Tableau, Excel
• SQL, database design, ETL pipelines
• Web scraping & API integration (BeautifulSoup, Selenium)
• Survey & qualitative research analysis (SPSS, MaxQDA)
• Structuring and writing data-driven research with strong methodology
đź“Š Typical projects I work on:
âś” Credit risk and churn prediction models
âś” Market behavior analysis & reporting
âś” Education and policy research based on real data
âś” Automating data workflows for small teams
GitHub portfolio → github.com/ShynggysTorez
🤝 I've worked with:
• Startups scaling through smarter analytics
• Academic teams writing advanced research reports
• Government and consulting clients using data for better strategies
My goal is always the same: to turn complex data into clear, explainable results that help people make decisions.
Let's connect if you're looking for someone who brings both data depth and communication clarity to the table.
Steps for completing your project
After purchasing the project, send requirements so Shynggys can start the project.
Delivery time starts when Shynggys receives requirements from you.
Shynggys works on your project following the steps below.
Revisions may occur after the delivery date.
Goal & dataset clarification
We define the objective (e.g. risk scoring, analysis) and confirm the dataset structure.
Data cleaning & preprocessing
I prepare your dataset (handle missing values, encode categories, etc.).