SAS Viya Natural Language Processing and Computer Vision — Information & Free Practice

The authority publishes percentage ranges for each content area. The practice percentages below use the midpoint of each range, normalized to 100%; they are not exact percentages published by the authority. Practice question counts may differ slightly because of rounding.

• Loading and Exploring Data — Official range: 18–22% (Practice allocation: 20%)

  • Import documents for analysis
  • Create and explore a project in SAS Visual Text Analytics
  • Load and prepare image data
• Identifying Text Patterns Using Natural Language Processing Techniques — Official range: 40–45% (Practice allocation: 42.5%)

  • Use the Concepts and Text Parsing Nodes to extract Terms and Concepts
  • Write Concept Rules
  • Use the Topics Node to extract machine-generated topics
  • Use rules to identify documents belonging to specific categories
  • Write Category rules
  • Use a Recurrent Neural Network (RNN) to recognize patterns
• Identifying Image Patterns Using Computer Vision Techniques — Official range: 35–40% (Practice allocation: 37.5%)

  • Use convolutional layers in a Convolutional Neural Network (CNN)
  • Use padding in a Convolutional Neural Network
  • Use pooling in a Convolutional Neural Network
  • Use fully connected layers in a Convolutional Neural Network
  • Use output layers in a Convolutional Neural Network
  • Tune the Hyperparameters of a Convolutional Neural Network
  • Score new image data
  • Explain the impact of various architectural designs
  • Use regularization techniques