Why it matters: How to train an AI in 2026: full pipeline, data, compute, fine-tuning, LoRA, RLHF, MLOps, risks, regulation, and future trends explained end to end.
Why it matters: Data augmentation expands training data with smart transforms and synthetic samples to cut overfitting and lift accuracy. See techniques, examples, and risks.