Exercise Robust Driver

"Robust Driver" is a term often used in machine learning to describe training methods that ensure a model performs reliably across various conditions, even when faced with unexpected or noisy data. It's like teaching a driver to stay safe and effective regardless of weather, road conditions, or distractions. By incorporating diverse scenarios into training, the model becomes more resilient, reducing errors when encountering new, unpredictable data in real-world applications. Essentially, it emphasizes building robustness into the model's ability to generalize well beyond its training environment.