following is the most accurate description of "zero -shot learning"?
D. RNNs are typically used for image processing tasks because of their ability to capture spatial information. E. The hidden state in RNNs is discarded after each forward pass, meaning that it doesn't affect the predictions made at subsequent timesteps. Explanation: B: RNNs are particularly good at handling sequential data where the order of data points is crucial, such as in speech recognition or language translation tasks. C: RNNs suffer from the vanishing gradient problem, especially when dealing with long sequences, which can make training difficult over time. This problem hinders the model's ability to learn long-term dependencies. Which statement accurately describes the purpose and function of the self-attention mechanism in Transformers?
training dataset but poorly on the test dataset. This behavior indicates that the model has learned the training data too well, including noise and outliers, and fails to generalize to new data. Which of the following activation functions is most commonly used in the hidden layers of deep learning models, and why?
early layers. Which of the following operations is likely causing this issue, and what could you do to mitigate it?
C. Use Generative AI to fully automate customer responses without any human involvement to reduce operational costs. D. Implement post-processing steps to review and edit AI-generated content before it reaches the customer to ensure accuracy and appropriateness. Explanation: Implementing post-processing steps to review and edit AI-generated content ensures accuracy and appropriateness before it reaches the customer, helping to maintain the quality of interactions and adhere to regulatory standards. You are a business analyst at a retail company, and your team wants to build a machine learning model to forecast sales. However, your team lacks extensive data science expertise. You decide to explore Oracle Cloud Infrastructure’s AutoML capabilities to automatically generate and train a machine learning model. The data you have is organized in an Oracle Autonomous Data Warehouse, and you aim to get predictions quickly to make business decisions. Which of the following strategies would best help you leverage OCI’s AutoML capabilities to build and train a machine learning model for sales forecasting?
D. Fine-tuning adapts a general -purpose LLM to specialize in a particular domain by updating model parameters with domain -relevant data, improving performance on task -specific queries. Explanation: Fine-tuning adapts a general -purpose LLM to specialize in a particular domain by updating model parameters with domain -relevant data, which enhances performance on specific task-related queries. You are tasked with detecting objects in a set of images to classify them into different categories. Which Oracle Cloud Infrastructure (OCI) AI service would be the best solution for this requirement?
