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Thursday, December 01, 2022

New Book on Synthetic Data

The data is most often,  the thing.    Look forward to taking a look.

New Book: Synthetic Data

Published on November 28, 2022, By Vincent Granville

Author of Intuitive Machine Learning and Explainable AI.

84 articles

Synthetic data is used more and more to augment real-life datasets, enriching them and allowing black-box systems to correctly classify observations or predict values that are well outside of training and validation sets. In addition, it helps understand decisions made by obscure systems such as deep neural networks, contributing to the development of explainable AI. It also helps with unbalanced data, for instance in fraud detection. Finally, since synthetic data is not directly linked to real people or transactions, it offers protection against data leakage. Synthetic data also contributes to eliminating algorithm biases and privacy issues, and more generally, to increased security.

Terrain generation, evolution and morphing (in chapter 11)

This book is the culmination of years of research on the topic, by the author. Not only it integrates all the material from his previous book “Intuitive Machine Learning and explainable AI”, but it also contains all but the most advanced math from his book on stochastic simulations. The author also added more recent advances with applications to terrain generation (with animated data), synthetic universes and experimental math. The latter is an infinite source of synthetic data to build and benchmark new machine learning techniques. Conversely mathematics benefits from these techniques to uncover new insights related to the most famous unsolved math problems. Chapter 14 on the Riemann Hypothesis illustrates this point, with new state-of-the-art research results on the subject.  ... ' 

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