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I will generate gdpr compliant synthetic data for your ml models
Machine Learning Engineer for Generative AI and Synthetic Data
I am a Machine Learning Engineer specializing in Generative AI and Synthetic Data. Using dedicated local GPU hardware, I help companies or people bypass strict data privacy laws (GDPR/HIPAA) and solve...
About this Gig
Are strict data privacy laws (GDPR/HIPAA) or severe class imbalance blocking your Machine Learning projects?
I am a specialized Machine Learning Engineer with a strong academic and practical background in Generative AI. I help companies bypass data scarcity by generating 100% privacy-safe, highly realistic synthetic tabular data.
Why choose my service?
Unlike basic data augmentation, I use advanced Deep Learning models (like CTGAN) running on dedicated local GPU hardware to learn the complex multi-variate statistical distributions of your seed data. The result is a perfectly balanced synthetic clone that maintains high predictive power but contains absolutely zero real personal information.
What you get:
- High-Fidelity Synthetic Data: Ready-to-use CSV files to train your ML models.
- Perfect Class Balancing: Upsampling minority classes (e.g., fraud detection, rare diseases).
- Data Quality Report: A mathematical SDMetrics report proving the correlation and fidelity of the generated data.
- Source Code: Delivery of the trained model (Premium package).
Industries I specialize in: Healthcare, Fintech, and Heavy Industry.
Please message me before ordering to discuss your data!
Programming language:
Python
Frameworks:
Scikit-learn
•
Keras
•
PyTorch
•
Panda
Tools:
Jupyter Notebook
•
OpenCV
•
TensorFlow
•
Excel
•
Colab
FAQ
Is my original seed data secure and private?
Absolutely. I process all data locally on a dedicated machine equipped with a high-end GPU, not on shared public cloud servers. Once the synthetic dataset is generated and the project is approved, your original seed data is permanently deleted from my systems.
How do you prove the synthetic data is high quality?
For Standard and Premium packages, I deliver a comprehensive Data Quality Report using the SDMetrics framework. This report mathematically proves that the synthetic dataset preserves the multi-variate statistical properties and column correlations of your original data.
What format should I provide my original data in?
Please provide your seed data in CSV or Excel format. The data should be tabular and structured. If your data requires heavy cleaning before generation, please message me first so we can discuss the preprocessing steps.
Can you fix highly imbalanced datasets (e.g., 99% normal, 1% fraud)?
This is a core benefit of my service. I can specifically upsample your minority class (such as fraud cases or rare diseases) during the generation process. This provides you with a perfectly balanced synthetic dataset, which significantly improves the accuracy of your Machine Learning models.
How much original "seed" data do you need to start?
Generative Deep Learning models (like CTGAN) require a reasonable amount of data to learn complex multi-variate patterns. I recommend a minimum of 1,000 to 5,000 rows for good results. However, the more seed data you provide, the higher the mathematical fidelity of the final synthetic output.
Are you willing to sign a Non-Disclosure Agreement (NDA)?
Absolutely. I frequently work with sensitive tabular data for the Healthcare and Fintech industries, so I fully understand the importance of corporate compliance. I am more than happy to sign your company's NDA before you share any seed data with me.
