- Preparing data for Deep Learning models
- Selecting appropriate loss functions and neural network architectures
- Training and evaluating Deep Learning models for automotive tasks
- Sample applications including anomaly detection, image recognition, and Advanced Driver Assistance Systems (ADAS)
