All MCQs

The correct answer is deep learning is used for language modeling, translation, and text classification. This matches the Deep Learning course topic: NLP applications.

The correct answer is deep learning can map acoustic or sequential features to speech units or text. This matches the Deep Learning course topic: Speech recognition applications.

The correct answer is deep learning can be applied to image classification, detection, and segmentation. This matches the Deep Learning course topic: Computer vision applications.

The correct answer is googlenet/inception uses parallel filter operations to capture features at multiple scales. This matches the Deep Learning course topic: GoogleNet/Inception.

The correct answer is resnet uses skip connections to help train very deep networks. This matches the Deep Learning course topic: ResNet.

The correct answer is dropconnect randomly drops weights rather than neuron outputs during training. This matches the Deep Learning course topic: DropConnect.

The correct answer is batch normalization normalizes intermediate activations to stabilize and speed up training. This matches the Deep Learning course topic: Batch normalization.

The correct answer is dropout randomly disables units during training to reduce co-adaptation. This matches the Deep Learning course topic: Dropout.

The correct answer is data normalization scales or centers data to support stable training. This matches the Deep Learning course topic: Data normalization.

The correct answer is data augmentation creates modified training examples to improve robustness. This matches the Deep Learning course topic: Data augmentation.

The correct answer is a gan trains a generator and discriminator in an adversarial setting. This matches the Deep Learning course topic: GANs.

The correct answer is cudnn provides optimized gpu routines for deep neural network operations. This matches the Deep Learning course topic: CuDNN.