Amy Steier

Machine Learning Accuracy Using Synthetic Data

Can synthetic data really be used in machine learning? We explore the utility of synthetic data created from popular datasets and tested on popular ML algorithms.
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Transforms and Synthetics on Relational Databases

A walkthrough of our new multi-table transform and multi-table synthetics notebooks, which can be used independently or simultaneously.
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Copyright © 2022 Gretel.ai

Transforms and Multi-Table Relational Databases

How to de-identify a relational database for demo or pre-production testing environments while keeping the referential integrity of primary and foreign keys intact.
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Gretel’s New Data Privacy Score

Gretel releases industry standard synthetic tabular data privacy evaluation and risk-based scoring system.
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Comprehensive Data Cleaning for AI and ML

Learn to prepare tabular data for AI and ML with an end-to-end data cleaning workflow.
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How accurate is my synthetic data?

Gretel’s new synthetic report is here, featuring a high-level score and metrics to help you assess the quality of your synthetic data.
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Gretel's New Synthetic Performance Report

Gretel's Premium SDK now includes detailed reporting that shows you how accurate your synthetic data's statistical distributions and correlations are.
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Copyright 2021 Gretel

Introducing Gretel's Privacy Filters

Create synthetic data that’s safer than ever. Our simple configuration file settings enable you to secure both your data and model from adversarial attacks.
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Copyright (c) 2021 Gretel

Optuna Your Model Hyperparameters

We explore the popular open-source package Optuna to demonstrate how you can optimize your model hyperparameters and build the best synthetic model possible.
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Innovating With FastText and Table Headers

Look at how FastText word embeddings can help to quickly understand new datasets, and build more consistent labels for your own data.
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