How to Make Synthetic Data | Synthetic Data Generation for Machine Learning

The video tutorial covers synthetic data generation, its benefits, and challenges. It explains how synthetic data can expand training datasets and improve model robustness. The tutorial demonstrates using Sklearn for simple data generation, data augmentation with Fashion-MNIST, and explores generative adversarial networks (GANs) for creating synthetic MNIST digits. It also highlights the use of Weights and Biases for data visualization and tracking metrics.

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