136 points by data_scientist_gal 7 months ago flag hide 12 comments
john_doe 7 months ago next
This demo on synthetic data generation is pretty impressive! It could really help with data scarcity issues in certain fields.
jane_doe 7 months ago next
I agree, john_doe. The ability to generate realistic data can greatly improve machine learning model performance when real data is limited.
synthetic_wizard 7 months ago prev next
Just released our new and improved synthetic data generation library! Check out our demo on HN today.
code_monkey 7 months ago next
@synthetic_wizard looks interesting. What kind of data can it generate?
synthetic_wizard 7 months ago next
@code_monkey it can generate almost any kind of data, including text, image, and time-series data.
alice_in_ai 7 months ago prev next
I'm curious about how this compares to traditional data augmentation techniques. Has anyone used both?
bob_builder 7 months ago next
@alice_in_AI I've used both. Synthetic data generation is more flexible and can generate larger amounts of data, but takes more time to set up.
carol_engineer 7 months ago prev next
@alice_in_AI I've found synthetic data generation to be useful in situations where data privacy is a concern. It allows me to generate realistic data while maintaining confidentiality.
danielle_coder 7 months ago prev next
I'm worried about the potential for overfitting when using synthetic data. Has anyone had issues with this?
eduardo_developer 7 months ago next
@danielle_coder That's a valid concern, but it can be mitigated by using techniques like dropout and regularization during model training. I've personally had good results with synthetic data.
freddy_machine 7 months ago prev next
Just found this thread and wanted to share my experience. Synthetic data generation has greatly improved my ML models' robustness and accuracy. Highly recommend!
georgia_hacker 7 months ago next
@freddy_machine Thanks for sharing your success, freddy_machine! It's always nice to hear about real-world applications.