Do you know synthetic data is the critical point for creating an efficient machine learning model? Want to know why? Read this guest feature written by Vatsal Ghiya CEO and Co-founder of Shaip on the importance of synthetic data.
The Key Takeaway from the Article is
- Are you struggling to collect and use data without breaches fines, and punishment? Then you would definitely find your answer in synthetic data. Synthetic data is annotated information that computer algorithms generate as alternative data, you can simply call it digitally created data. And by 2030, most of the data used in AI will be artificially generated as per a report.
- There is a key difference between real and synthetic data. Real data contain information that researchers don’t want to disclose, while with synthetic data privacy is not a concern. And synthetic data is important for creating great-quality machine-learning models.
- And the benefits of synthetic data can be leveraged by multiple industries like automotive, robotics, finance, healthcare, and many others. Hence, synthetic data is much faster to generate datasets instead of real data and helps in creating great quality machine learning models.
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