I will generate privacy safe synthetic datasets for ai training
Ethical Web Scraping and World Class Datasets Delivery
Certifié par Fiverr Pro
Kanchanak a été sélectionné par l'équipe Fiverr Pro pour son expertise.
Certifié pour
Data science et machine learning
À propos de ce service
Vetted Pro
High-performing AI models require high-quality training data!
However, using real user data often carries significant privacy risks and compliance hurdles (GDPR, HIPAA). Generic synthetic tools often fail to capture the complex correlations and edge cases that your models need to learn effectively.
The Solution: Secure, High-Fidelity Synthetic Data
I specialize in generating privacy-compliant synthetic datasets that mathematically mirror your original data's statistical properties without exposing sensitive information. Using dedicated local hardware (RTX 5080) I ensure your data is processed offline and remains secure.
Deliverables:
- Privacy-Safe Data: Retains the statistical DNA of your original dataset with zero real user information.
- Fidelity Verification: Includes a statistical report (KS-tests, Correlation Matrices) to confirm distribution accuracy.
- AI-Ready Formats: Structured specifically for LLM fine-tuning (JSONL) or standard ML (CSV/Parquet).
Professional Credentials:
- Fiverr Vetted Pro: Verified for advanced data expertise.
- Kaggle Grandmaster: Globally ranked #2 in Datasets.
- Secure Infrastructure: All computation is performed on a secure private workstation
Frameworks:
Scikit-learn
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keras
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PyTorch
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Panda
•
Autres
Type de données:
Texte
Langage de programmation:
Python
Outils:
Jupyter Notebook
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tensorflow
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Excel
•
Autres
APIs:
OpenAI
•
Autres
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FAQ
Is my data safe? Does it go to the cloud?
Your data is processed 100% locally on my secure, offline RTX 5080 workstation. It is never uploaded to third-party cloud generators. I delete all client source files 7 days after order completion.
Is my data safe? Does it go to the cloud?
Yes. I can deliver the final dataset in JSONL format specifically structured for OpenAI or HuggingFace fine-tuning jobs.
How do I know the synthetic data is "good"?
Every order includes a "Statistical Fidelity Report." I run Kolmogorov-Smirnov tests to prove that the synthetic columns have the exact same mathematical properties as your original data.
What if I don't have a dataset yet?
I can generate data entirely from scratch based on your business rules. (e.g., "Create 50,000 loan applicants with realistic credit scores, debt-to-income ratios, and default histories"). Please message me first to discuss your specific schema.

