Oracle Cloud Infrastructure 2025 AI Foundations Associate Free Sample Questions

Structured data fits neatly into rows and columns (databases). Unstructured data does not have a predefined model and includes text-heavy documents (PDFs), images, and audio/video files. Semi-structured data would be formats like JSON or XML.

Supervised learning involves training a model on a labeled dataset, where the correct output (in this case, 'fraud' or 'not fraud') is known. The model learns the relationship between input features and the target label.

Narrow AI (or Weak AI) is designed to perform a specific task or a limited set of tasks efficiently, such as voice recognition or recommendation systems, but lacks general cognitive abilities.

Convolutional layers apply filters (kernels) to the input image to create feature maps, detecting patterns like edges, shapes, and textures. Pooling layers reduce dimensionality, and fully connected layers perform the final classification.

Overfitting occurs when a model learns the training data too closely, including its noise and outliers, resulting in poor performance on new data (high variance). Underfitting is when the model is too simple to capture the underlying pattern (high bias).

OCI Language provides pre-trained models for text analysis, including Named Entity Recognition (NER) which can identify and redact PII entities like names, addresses, and phone numbers from unstructured text.