How to Use Synthetic and Simulated Data Effectively

Using synthetic data isn’t exactly a new practice: it’s been a productive approach for several years now, providing practitioners with the data they need for their projects in situations where real-world datasets prove inaccessible, unavailable, or limited from a copyright or approved-use perspective.

The recent rise of LLMs and AI-generated tools has transformed the synthetic-data scene, however, just as it has numerous other workflows for machine learning and data science professionals. This week, we’re presenting a collection of recent articles …

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