OFFICIAL ORACLE 1Z0-1122-24 STUDY GUIDE & LATEST 1Z0-1122-24 TEST PRACTICE

Official Oracle 1z0-1122-24 Study Guide & Latest 1z0-1122-24 Test Practice

Official Oracle 1z0-1122-24 Study Guide & Latest 1z0-1122-24 Test Practice

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Oracle 1z0-1122-24 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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.
Topic 2
  • 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 3
  • 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 4
  • OCI Generative AI and Oracle 23ai: This section covers CI Generative AI Services that are a key component of Oracle's AI offerings, and exploring these services provides a clear understanding of how Oracle supports generative AI applications.
Topic 5
  • Intro to AI Foundations: This section covers the fundamentals of AI are essential for understanding its wide-ranging impact and applications.

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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q16-Q21):

NEW QUESTION # 16
Which statement describes the Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure Document Understanding?

  • A. It provides real-time translation of text.
  • B. It converts audio files into text.
  • C. It enhances the visual quality of documents.
  • D. It recognizes and extracts text from a document.

Answer: D

Explanation:
The Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure (OCI) Document Understanding recognizes and extracts text from documents. This capability is fundamental for converting printed or handwritten text into a machine-readable format, allowing for further processing, such as text analysis, search, and archiving. OCI's OCR is an essential tool in automating document processing workflows, enabling businesses to digitize and manage their documents efficiently.


NEW QUESTION # 17
What is a key advantage of using dedicated AI clusters in the OCI Generative AI service?

  • A. They provide faster internet connection speeds.
  • B. They allow access to unlimited database resources.
  • C. They are free of charge for all users.
  • D. They provide high performance compute resources for fine-tuning tasks.

Answer: D

Explanation:
The primary advantage of using dedicated AI clusters in the Oracle Cloud Infrastructure (OCI) Generative AI service is the provision of high-performance compute resources that are specifically optimized for fine-tuning tasks. Fine-tuning is a critical step in the process of adapting pre-trained models to specific tasks, and it requires significant computational power. Dedicated AI clusters in OCI are designed to deliver the necessary performance and scalability to handle the intense workloads associated with fine-tuning large language models (LLMs) and other AI models, ensuring faster processing and more efficient training.


NEW QUESTION # 18
What is the purpose of the model catalog in OCI Data Science?

  • A. To create and switch between different environments
  • B. To store, track, share, and manage models
  • C. To provide a preinstalled open source library
  • D. To deploy models as HTTP endpoints

Answer: B

Explanation:
The primary purpose of the model catalog in OCI Data Science is to store, track, share, and manage machine learning models. This functionality is essential for maintaining an organized repository where data scientists and developers can collaborate on models, monitor their performance, and manage their lifecycle. The model catalog also facilitates model versioning, ensuring that the most recent and effective models are available for deployment. This capability is crucial in a collaborative environment where multiple stakeholders need access to the latest model versions for testing, evaluation, and deployment.


NEW QUESTION # 19
What is the main function of the hidden layers in an Artificial Neural Network (ANN) when recognizing handwritten digits?

  • A. Directly predicting the final output
  • B. Providing labels for the output neurons
  • C. Capturing the internal representation of the raw image data
  • D. Storing the input pixel values

Answer: C

Explanation:
In an Artificial Neural Network (ANN) designed for recognizing handwritten digits, the hidden layers serve the crucial function of capturing the internal representation of the raw image data. These layers learn to extract and represent features such as edges, shapes, and textures from the input pixels, which are essential for distinguishing between different digits. By transforming the input data through multiple hidden layers, the network gradually abstracts the raw pixel data into higher-level representations, which are more informative and easier to classify into the correct digit categories.


NEW QUESTION # 20
What is the primary benefit of using the OCI Language service for text analysis?

  • A. It allows for text analysis at scale without machine learning expertise.
  • B. It provides image processing capabilities.
  • C. It only works with structured data.
  • D. It requires extensive machine learning expertise to use.

Answer: A

Explanation:
The primary benefit of using the OCI Language service for text analysis is its ability to scale text analysis without requiring users to have extensive machine learning expertise. The service abstracts the complexities of machine learning, allowing businesses to easily process and analyze large amounts of text data through pre-built models. This accessibility makes it possible for a broader range of users to leverage advanced text analysis capabilities, facilitating insights from textual data without needing to develop and train models from scratch.


NEW QUESTION # 21
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