Are you ready to be a Computer Vision Engineer?

What this check covers

• 1

  Generalisation

  Overfitting is especially problematic in CV where models memorise texture patterns.

• 2

  Evaluation

  Proper train/test splitting prevents inflated accuracy claims in image classification.

• 3

  Metrics

  Object detection tasks are inherently imbalanced — raw accuracy is almost always misleading.

• 4

  Optimisation

  Understanding gradient flow is critical for training deep convolutional networks.

• 5

  Regularisation

  Dropout and weight decay are standard tools for training vision models.