Evaluating Synthetic Data with Post-Processing Techniques


Synthetic data has become increasingly valuable in machine learning and data science, but its quality and fidelity to real-world data are paramount for its effectiveness. The session objectives are (1) to introduce the attendees to the post-processing techniques that can aid in evaluating the usefulness of Synthetic datasets and (2) to learn how to apply these post-processing techniques using the Rendered.ai Platform.

The post-processing techniques include dimensionality reduction using UMAP (Uniform Manifold Approximation and Projection), dataset augmentation with GANs (Generative Adversarial Networks), analyses of mean brightness within the datasets, and object metrics and properties analyses.

These post-processing techniques not only refine synthetic data but also provide critical insights into its quality and suitability for downstream applications. By understanding these techniques, attendees will be better equipped to assess and optimize synthetic datasets, thereby improving their efficacy in real-world machine learning scenarios.

Session Outline:

Attendees will learn about the various post processing techniques : UMAP, GAN, Mean brightness analyses, Object Metrics analyses, and Properties analyses and also how to apply them to their synthetic datasets.

The tools used are the Rendered.ai Platform and anatools Python package


I'm a Software Engineer and Platform Release Manager with 8+ years of experience in development projects across diverse tech environments. I currently work at Rendered.ai, where I lead platform upgrades, maintain our Python SDK, and ensure platform reliability. I've developed new features, deployed and managed upgrades, built deployment pipelines, and led beta testing sessions for the Rendered.ai PaaS.

Before that, I worked at Cisco Webex, where I developed tools for automation and monitoring for storage devices. I've also worked at Toshiba Global Commerce Solutions, Samsung Austin Semiconductor, and Fidelity Investments.

I'm pursuing an M.S. in Computer Science with a specialization in Interactive Intelligence at Georgia Institute of Technology and hold dual B.S. degrees in Computer Engineering and Electrical Engineering from North Carolina State University.

Currently, I live in Rhode Island, USA with my husband and dog. In my free time, I enjoy gaming and making music. I can also bake a mean vegan pumpkin pie.

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