여러분은 우리. DumpTOP의Oracle 1Z0-1122-25시험자료 즉 덤프의 문제와 답만 있으시면Oracle 1Z0-1122-25인증시험을 아주 간단하게 패스하실 수 있습니다.그리고 관련 업계에서 여러분의 지위상승은 자연적 이로 이루어집니다. DumpTOP의 덤프를 장바구니에 넣으세요. 그리고 DumpTOP에서는 무료로 24시간 온라인상담이 있습니다.
Oracle 1Z0-1122-25 시험요강:
주제
소개
주제 1
Intro to Generative AI & LLMs: This section tests the abilities of AI Developers to understand generative AI and large language models. It introduces the principles of generative AI, explains the fundamentals of large language models (LLMs), and discusses the core workings of transformers, prompt engineering, instruction tuning, and LLM fine-tuning for optimizing AI-generated content.
주제 2
Intro to AI Foundations: This section of the exam measures the skills of AI Practitioners and Data Analysts in understanding the fundamentals of artificial intelligence. It covers key concepts, AI applications across industries, and the types of data used in AI models. It also explains the differences between artificial intelligence, machine learning, and deep learning, providing clarity on how these technologies interact and complement each other.
주제 3
Get started with OCI AI Portfolio: This section measures the proficiency of Cloud AI Specialists in exploring Oracle Cloud Infrastructure (OCI) AI services. It provides an overview of OCI AI and machine learning services, details AI infrastructure capabilities and explains responsible AI principles to ensure ethical and transparent AI development.
주제 4
Intro to OCI AI Services: This section tests the expertise of AI Solutions Engineers in working with OCI AI services and related APIs. It provides insights into key AI services such as language processing, computer vision, document understanding, and speech recognition, allowing professionals to leverage Oracle’s AI ecosystem for building intelligent applications.
주제 5
Intro to DL Foundations: This section assesses the expertise of Deep Learning Engineers in understanding deep learning frameworks and architectures. It covers fundamental concepts of deep learning, introduces convolutional neural networks (CNN) for image processing, and explores sequence models like recurrent neural networks (RNN) and long short-term memory (LSTM) networks for handling sequential data.
DumpTOP는 여러분이 원하는 최신 최고버전의 Oracle 인증1Z0-1122-25덤프를 제공합니다. Oracle 인증1Z0-1122-25덤프는 IT업계전문가들이 끊임없는 노력과 지금까지의 경험으로 연구하여 만들어낸 제일 정확한 시험문제와 답들로 만들어졌습니다. DumpTOP의 문제집으로 여러분은 충분히 안전이 시험을 패스하실 수 있습니다. 우리 DumpTOP 의 문제집들은 모두 100%합격율을 자랑하며 DumpTOP의 제품을 구매하였다면 Oracle 인증1Z0-1122-25시험패스와 자격증 취득은 근심하지 않으셔도 됩니다. 여러분은 IT업계에서 또 한층 업그레이드 될것입니다.
최신 Oracle Cloud Infrastructure 1Z0-1122-25 무료샘플문제 (Q23-Q28):
질문 # 23 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 deploy models as HTTP endpoints
D. To provide a preinstalled open source library
정답：B
설명： 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.
질문 # 24 Which feature is NOT supported as part of the OCI Language service's pretrained language processing capabilities?
A. Text Classification
B. Sentiment Analysis
C. Text Generation
D. Language Detection
정답：C
설명： The OCI Language service offers several pretrained language processing capabilities, including Text Classification, Sentiment Analysis, and Language Detection. However, it does not natively support Text Generation as a part of its core language processing capabilities. Text Generation typically involves creating new content based on input prompts, which is a feature more commonly associated with models specifically designed for natural language generation.
질문 # 25 Which AI Ethics principle leads to the Responsible AI requirement of transparency?
A. Prevention of harm
B. Explicability
C. Respect for human autonomy
D. Fairness
정답：B
설명： Explicability is the AI Ethics principle that leads to the Responsible AI requirement of transparency. This principle emphasizes the importance of making AI systems understandable and interpretable to humans. Transparency is a key aspect of explicability, as it ensures that the decision-making processes of AI systems are clear and comprehensible, allowing users to understand how and why a particular decision or output was generated. This is critical for building trust in AI systems and ensuring that they are used responsibly and ethically. Top of Form Bottom of Form
질문 # 26 Which algorithm is primarily used for adjusting the weights of connections between neurons during the training of an Artificial Neural Network (ANN)?
A. Random Forest
B. Support Vector Machine
C. Backpropagation
D. Gradient Descent
정답：C
설명： Backpropagation is the algorithm primarily used for adjusting the weights of connections between neurons during the training of an Artificial Neural Network (ANN). It is a supervised learning algorithm that calculates the gradient of the loss function with respect to each weight by applying the chain rule, propagating the error backward from the output layer to the input layer. This process updates the weights to minimize the error, thus improving the model's accuracy over time. Gradient Descent is closely related as it is the optimization algorithm used to adjust the weights based on the gradients computed by backpropagation, but backpropagation is the specific method used to calculate these gradients.
질문 # 27 Which is NOT a capability of OCI Vision's image analysis?
A. Translating text in images to another language
B. Assigning classification labels to images
C. Object detection with bounding boxes
D. Locating and extracting text in images
정답：A
설명： 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. Top of Form Bottom of Form
질문 # 28 ......
우리DumpTOP에서는 각종IT시험에 관심있는분들을 위하여, 여러 가지 인증시험자료를 제공하는 사이트입니다. 우리DumpTOP는 많은 분들이 IT인증시험을 응시하여 성공할수록 도와주는 사이트입니다. 우리의 파워는 아주 대단하답니다. 여러분은 우리DumpTOP 사이트에서 제공하는Oracle 1Z0-1122-25관련자료의 일부분문제와답등 샘플을 무료로 다운받아 체험해봄으로 우리에 믿음이 생기게 될 것입니다.
