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Generating realistic location data for users for testing or modeling simulations is a hard problem. Current approaches just create random locations inside a box, placing users in waterways or on top of buildings. This inability to make accurate, synthetic location data stifles a lot of innovative projects that require diverse and complex datasets to fuel their work.
Using Python with Gretel.ai to Generate Synthetic Location Data by Alex Watson, co-founder and CPO, Gretel.ai