concept:augmentation
Augmentation
Augmentation in the context of production machine-learning systems.
Lessons
Formal explanations, examples, simulations, and checkpoints.
Image ML
Receptive fields, normalization, and residuals
Depth works when context grows deliberately and identity paths keep shapes and gradients connected.
Image MLTransfer learning for classification, detection, and segmentation
Transfer the representation in measured stages, while letting the required output and leakage-safe split define the task.
Image MLVision in the wild: thresholds, latency, and drift
Production vision is a thresholded, timed, monitored decision system—not an accuracy number attached to a model file.
Courses & assignments
Dependency-authoritative learning units.
Casebook
Reported facts and course reconstructions.