RELIABLE 1Z0-1122-24 EXAM SIMS, 1Z0-1122-24 EXAM SAMPLE QUESTIONS

Reliable 1z0-1122-24 Exam Sims, 1z0-1122-24 Exam Sample Questions

Reliable 1z0-1122-24 Exam Sims, 1z0-1122-24 Exam Sample Questions

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Tags: Reliable 1z0-1122-24 Exam Sims, 1z0-1122-24 Exam Sample Questions, 1z0-1122-24 Training Courses, Learning 1z0-1122-24 Materials, Exam 1z0-1122-24 Answers

These 1z0-1122-24 PDF Questions are being presented in practice test software and PDF dumps file formats. The Oracle 1z0-1122-24 desktop practice test software is easy to use and install on your desktop computers. Whereas the other 1z0-1122-24 web-based practice test software is concerned, this is a simple browser-based application that works with all operating systems. Both practice tests are customizable, simulate actual exam scenarios, and help you overcome mistakes.

Oracle 1z0-1122-24 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Intro to OCI AI Services: This section is about exploring OCI AI Services and their related APIs, such as those for Language, Vision, Document Understanding, and Speech, which are essential for developers and businesses looking to integrate AI into their operations.
Topic 2
  • Intro to ML Foundations: This section covers Machine Learning (ML) which is a critical area within AI, and understanding its fundamentals is crucial for anyone interested in this field. The section covers delving into the basics of ML allowing for a better grasp of how machines learn from data.
Topic 3
  • Intro to DL Foundations: This section covers Deep Learning (DL) is a subset of ML that focuses on neural networks with many layers, and understanding its core concepts is vital for working with complex models.
Topic 4
  • Get Started with OCI AI Portfolio: This section is about the OCI AI Portfolio which offers a comprehensive suite of services and infrastructure for developing and deploying AI models. Exploring the overview of OCI AI Services provides insight into the tools available for AI development.

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2025 Perfect Reliable 1z0-1122-24 Exam Sims | Oracle Cloud Infrastructure 2024 AI Foundations Associate 100% Free Exam Sample Questions

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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q15-Q20):

NEW QUESTION # 15
Which statement best describes the relationship between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL)?

  • A. ML is a subset of AI, and DL is a subset of ML.
  • B. AI is a subset of DL, which is a subset of ML.
  • C. DL is a subset of AI, and ML is a subset of DL.
  • D. AI, ML, and DL are entirely separate fields with no overlap.

Answer: A

Explanation:
Artificial Intelligence (AI) is the broadest field encompassing all technologies that enable machines to perform tasks that typically require human intelligence. Within AI, Machine Learning (ML) is a subset focused on the development of algorithms that allow systems to learn from and make predictions or decisions based on data. Deep Learning (DL) is a further subset of ML, characterized by the use of artificial neural networks with many layers (hence "deep").
In this hierarchy:
AI includes all methods to make machines intelligent.
ML refers to the methods within AI that focus on learning from data.
DL is a specialized field within ML that deals with deep neural networks.


NEW QUESTION # 16
Which feature of OCI Speech helps make transcriptions easier to read and understand?

  • A. Text normalization
  • B. Audio tuning
  • C. Profanity filtering
  • D. Timestamping

Answer: A

Explanation:
The text normalization feature of OCI Speech helps make transcriptions easier to read and understand by converting spoken language into a more standardized and grammatically correct format. This process includes correcting grammar, punctuation, and formatting, ensuring that the transcribed text is clear, accurate, and suitable for various use cases. Text normalization enhances the usability of transcriptions, making them more accessible and easier to process in downstream applications.
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NEW QUESTION # 17
Which capability is supported by the Oracle Cloud Infrastructure Vision service?

  • A. Generating realistic images from text
  • B. Detecting and preventing fraud in financial transactions
  • C. Analyzing historical data for unusual patterns
  • D. Detecting vehicle number plates to issue speed citations

Answer: D

Explanation:
The Oracle Cloud Infrastructure (OCI) Vision service is designed for image analysis tasks, which includes the capability to detect and recognize objects, such as vehicle number plates. This functionality is particularly useful for applications such as automated enforcement of traffic laws, where the system can identify vehicles exceeding speed limits and issue citations based on the detected number plates. This capability leverages advanced computer vision techniques to process and analyze visual data, making it suitable for applications in public safety, transportation, and law enforcement.


NEW QUESTION # 18
Which is NOT a capability of OCI Vision's image analysis?

  • A. Locating and extracting text in images
  • B. Assigning classification labels to images
  • C. Object detection with bounding boxes
  • D. Translating text in images to another language

Answer: D

Explanation:
OCI Vision's image analysis capabilities include locating and extracting text from images, assigning classification labels to images, and detecting objects with bounding boxes. However, translating text in images to another language is not a capability of OCI Vision's image analysis. This functionality typically requires an additional layer of processing, such as integration with a language translation service, which is beyond the scope of OCI Vision's core image analysis features.
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NEW QUESTION # 19
What key objective does machine learning strive to achieve?

  • A. Explicitly programming computers
  • B. Improving computer hardware
  • C. Creating algorithms to solve complex problems
  • D. Enabling computers to learn and improve from experience

Answer: D

Explanation:
The key objective of machine learning is to enable computers to learn from experience and improve their performance on specific tasks over time. This is achieved through the development of algorithms that can learn patterns from data and make decisions or predictions without being explicitly programmed for each task. As the model processes more data, it becomes better at understanding the underlying patterns and relationships, leading to more accurate and efficient outcomes.


NEW QUESTION # 20
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