Synthetic Data and Generative AI by Vincent Granville (.ePUB)+

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File Size: 43.9 MB

Synthetic Data and Generative AI by Vincent Granville
Requirements: .ePUB, .PDF reader, 43.9 MB, 19.1 MB | True PDF, ePUB
Overview: Synthetic Data and Generative AI covers the foundations of Machine Learning, with modern approaches to solving complex problems and the systematic generation and use of synthetic data. Emphasis is on scalability, automation, testing, optimizing, and interpretability (explainable AI). For instance, regression techniques – including logistic and Lasso – are presented as a single method, without using advanced linear algebra. Confidence regions and prediction intervals are built using parametric bootstrap, without statistical models or probability distributions. Models (including generative models and mixtures) are mostly used to create rich synthetic data to test and benchmark various methods. I provide Python code and synthetic data generators for replication purposes.
Genre: Non-Fiction > Tech & Devices

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