Part 12/17:
Supervised learning still dominates, making accurate labeling critical. Manual annotation is costly; hence, semi-automated approaches using pre-trained models generate labeled data, which is then corrected by human reviewers. Tools for efficient labeling and quality control are essential to prevent "garbage in, garbage out."
Synthetic Data & Data Augmentation
Synthetic data generation, via Generative Adversarial Networks (GANs), offers a potent way to augment datasets, simulate edge cases, and validate models before deployment.