track:vision-multimodal

Vision Multimodal

Vision Multimodal in the context of production machine-learning systems.

Lessons

Formal explanations, examples, simulations, and checkpoints.

Use images are data contracts to move the vision production brief toward a defensible release.

Use convolution under the microscope to move the vision production brief toward a defensible release.

Use receptive fields, normalization, and residuals to move the vision production brief toward a defensible release.

Use transfer learning for classification, detection, and segmentation to move the vision production brief toward a defensible release.

Use vision in the wild: thresholds, latency, and drift to move the vision production brief toward a defensible release.

Dependency-authoritative learning units.

CNN and transfer-learning baselines with augmentation, calibration, and monitoring.

Assignment: Rare-defect vision system

Reported facts and course reconstructions.