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Synthetic Data: Insights, updates and more
Learn more about synthetic data, our product and successful use cases
The SDV Flights Synthesizer: Generative AI for Flight Scenarios
Use the SDV Flights Synthesizer to simulate disruptive scenarios and improve software resilience.
The SDV in 2022: Never a Dull Moment
A 2022 year-end review of the SDV and what you can expect in 2023.
Categorical Data: A Closer Look
Understand categorical data to help you create higher quality synthetic data
3 user-centric growth strategies for open source
Our open source grew faster when we adopted a user-centric mindset. Here are 3 strategies we used along the way.
The Most Important Open Source Demographic That No One Thinks About
How we define a user in 2023 to build a community around synthetic data.
Can you use synthetic data for label balancing?
Imbalanced data can prevent your projects from succeeding. Will synthetic data work? Explore the rationale behind label balancing.
Interpreting the Progress of CTGAN
It can be difficult to verify the progress that a GAN is making. What if we combined it with easily interpretable metrics and visualizations?
How to evaluate synthetic data quality for your project — and avoid the biggest mistake we see
Evaluating synthetic data quality is critical. Avoid this common mistake and lead your project to success.
ML Model Development using Synthetic Data Clones
What happens when you train a machine learning model on synthetic data instead of real data? Let's experiment to find out.
Building the Unique Combinations Constraint in the SDV
Sometimes, you want to limit the amount of permutations in your synthetic data. Explore the strategies we used for enforcing this kind of logic.
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