Free Oracle 1Z0-184-25 Exam Questions
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Oracle 1Z0-184-25 Exam Questions
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Provided By: Oracle
- Exam: Oracle Database 23ai AI Professional - Early Access
- Certification: Oracle Database
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Total Questions: 108
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Updated On: Apr 25, 2025
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Rated: 4.9 |
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Online Users: 216
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Question 1
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You are tasked with creating a table to store vector embeddings with the following characteristics:
Each vector must have exactly 512 dimensions, and the dimensions should be stored as 32-bitfloating
point numbers. Which SQL statement should you use?
Answer: D
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You are tasked with creating a table to store vector embeddings with the following characteristics:
Each vector must have exactly 512 dimensions, and the dimensions should be stored as 32-bitfloating
point numbers. Which SQL statement should you use?
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Question 2
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What is the correct order of steps for building a RAG application using PL/SQL in Oracle Database
23ai?
Answer: B
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What is the correct order of steps for building a RAG application using PL/SQL in Oracle Database
23ai?
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Question 3
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You are tasked with creating a table to store vector embeddings with the following characteristics:
Each vector must have exactly 512 dimensions, and the dimensions should be stored as 32-bitfloating
point numbers. Which SQL statement should you use?
Answer: D
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You are tasked with creating a table to store vector embeddings with the following characteristics:
Each vector must have exactly 512 dimensions, and the dimensions should be stored as 32-bitfloating
point numbers. Which SQL statement should you use?
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Question 4
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How does an application use vector similarity search to retrieve relevant information from a
database, and how is this information then integrated into the generation process?
Answer: A
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How does an application use vector similarity search to retrieve relevant information from a
database, and how is this information then integrated into the generation process?
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Question 5
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A machine learning team is using IVF indexes in Oracle Database 23ai to find similar images in a large
dataset. During testing, they observe that the search results are often incomplete, missing relevant
images. They suspect the issue lies in the number of partitions probed. How should they improve the
search accuracy?
Answer: A
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A machine learning team is using IVF indexes in Oracle Database 23ai to find similar images in a large
dataset. During testing, they observe that the search results are often incomplete, missing relevant
images. They suspect the issue lies in the number of partitions probed. How should they improve the
search accuracy?