NCA-GENM 무료 덤프문제 온라인 액세스

In convolutional neural networks, we may use padding in both convolution and transposed convolution.
Which two (2) statements accurately describe padding in convolution and transposed convolution? Pick the 2 correct responses below.

• A.Padding in convolution is used only when the input image is smaller than the filter size, while padding in transposed convolution is used only when the input image is larger than the filter size.
• B.Padding in convolution increases the spatial dimensions of the input feature map, while padding in transposed convolution decreases the spatial dimensions of the output feature maps.
• C.Padding in convolution enables convolution operations on the boundary pixels of the input. In transposed convolution, it removes rows and columns along the perimeter of the input after it is expanded with stride.
• D.Padding in convolution and transposed convolution serve the same purpose of reducing the convolutional neural network's memory requirement and computational cost of the convolutional neural network.
• E.In a convolution operation, padding is added to the output after it has been expanded with the stride. On the other hand, in a transposed convolution operation, padding is added to the input before it is expanded with stride.

What is the significance of A/B testing in ML software engineering?

• A.A/B testing helps in evaluating the performance and effectiveness of different machine learning models.
• B.A/B testing is irrelevant in ML software engineering.
• C.A/B testing is used to measure the impact of changes in the user interface of a ML application.
• D.A/B testing helps in optimizing the hyperparameters of a machine learning model.

What is the role of CLIP (Contrastive Language-Image Pretraining) in text-to-image generation?

• A.CLIP provides a common embedding space for both the textual and image modalities.
• B.CLIP is used to convert textual input into image embeddings.
• C.CLIP is used to generate image captions from textual input.
• D.CLIP is used to enhance datasets through data augmentation for text-to-image generation.

What is a main application of Triton Inference Server?

• A.Triton Server can be used to deploy AI models on the GPU only.
• B.Triton Server can be used to generate images from pure noise.
• C.Triton Server can be used to execute GPU-accelerated graph analysis with cuGraph.
• D.Triton Server can be used to deploy neural networks from various frameworks.

You have been given a dataset with missing values. What is the first step you should take with the data?

• A.Fill in the missing values with a default value.
• B.Analyze the patterns and distribution of missing values.
• C.Remove the rows with missing values.
• D.Remove the columns with missing values.