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1Z0-1127-24 : Oracle Cloud Infrastructure 2024 Generative AI Professional- 100% pass 

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Hi Friends,
Here we are sharing most repeated Oracle Cloud Infrastructure 2024
Generative AI Professional certification (1Z0-1127-24) dumps, it will help you to prepare for generative ai certification.
The Oracle Cloud Infrastructure 2024 Generative AI Professional certification validates your ability to leverage Oracle Cloud Infrastructure (OCI) to build and deploy generative AI applications. This certification is ideal for IT professionals with experience in OCI who want to specialize in the rapidly growing field of generative AI. Generative AI allows computers to create entirely new content, from realistic images and videos to creative text formats like poems or scripts.
Oracle Cloud Generative AI Professional (1Z0-1127-24) Exam Questions Topics:
The 1Z0-1127-24 exam covers a range of generative AI concepts and their implementation within OCI. Here’s a breakdown of some key areas:
Generative AI Fundamentals: Understand the core concepts of generative AI, including different generative models and their capabilities.
Oracle Generative AI Service: Deep dive into the functionalities of Oracle’s Generative AI service, including building and managing Large Language Models (LLMs).
Retrieval Augmented Generation (RAG): Learn about RAG, a technique that combines retrieval-based and generative approaches for improved factual consistency.
LangChain Models: Explore LangChain, a framework for building creative text formats by chaining together different prompts and models.
Vector Databases and Semantic Search: Grasp the role of vector databases and semantic search in enabling efficient retrieval of relevant data for generative models.
Building, Deploying, and Evaluating LLM Applications: The exam will assess your ability to construct LLM applications using RAG and LangChain, deploy them within OCI, and evaluate their performance.
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Комментарии : 59   
@mohammedafrith4297
@mohammedafrith4297 Месяц назад
Que 43 - Correct answer is A
@pandu7820
@pandu7820 Месяц назад
Thanks for correcting 🙂
@aireddy
@aireddy Месяц назад
@@pandu7820 Here is why A is correct: Large Language Models (LLMs) without Retrieval Augmented Generation (RAG) are typically self-supervised models that rely on their internal knowledge and representations learned during pretraining on a large text corpus. They generate responses based solely on the information encoded in their model, without accessing external databases or retrieval systems. This is in contrast to RAG-based models, which use an external database or retrieval system to augment their generation capabilities.
@aireddy
@aireddy Месяц назад
38 B) TO PENALIZE TOKENS THAT HAVE ALREADY APPEARED, BASED ON THE NUMBER OF TIMES THEY HAVE BEEN USED Frequency penalties are a technique used in language models to control the repetition of tokens (words or subwords) and encourage more diverse output. The idea is to assign a penalty score to tokens that have already appeared in the text, with the frequency of their appearance determining the magnitude of the penalty. This helps to prevent the model from generating repetitive or unengaging text, and instead encourages it to use a wider range of vocabulary.
@SubtleDisastrousKaroakes
@SubtleDisastrousKaroakes Месяц назад
35 is D, It doesn't remove training cost completely, but it adds efficient approach. SO reduced cost.
@SubtleDisastrousKaroakes
@SubtleDisastrousKaroakes Месяц назад
62) Which is a key characteristic of the annotation process used in T-Few fine-tuning? A) T-Few fine tuning uses annotated data to adjust a fraction of model weights.
@AkashRawat-br2ew
@AkashRawat-br2ew Месяц назад
Que 38 - correct options should be B as per Oracle
@pandu7820
@pandu7820 Месяц назад
Sorry that is my mistake The correct answer is b
@SubtleDisastrousKaroakes
@SubtleDisastrousKaroakes Месяц назад
11B The cosine similarity value between embeddings provides insights into their relationships in vector space: 1: The embeddings are identical in direction. They are perfectly similar and have the same meaning or representation. 0: The embeddings are orthogonal, meaning they are at a 90-degree angle to each other. This indicates no similarity or correlation between them. -1: The embeddings are diametrically opposed, meaning they point in exactly opposite directions. This indicates a complete lack of similarity and an inverse relationship. These values help in understanding how closely related or different the embeddings are in terms of their semantic or contextual meaning.
@pandu7820
@pandu7820 Месяц назад
No in docs also mentioned option A
@Akkishiva
@Akkishiva Месяц назад
Que 35- correct answer is D
@aireddy
@aireddy Месяц назад
When using few-shot model prompting, the large language model (LLM) does not need to be retrained or use any additional computational resources. The examples provided in the prompt serve as a guide for the LLM to adapt its behavior and generate accurate outputs. So, option C "IT ELIMINATES THE NEED FOR ANY TRAINING OR COMPUTATIONAL RESOURCES" is actually a correct
@vasutamizhanda5184
@vasutamizhanda5184 Месяц назад
Accuracy of this video is 98.57... good job:)
@Siddharth-l9y
@Siddharth-l9y Месяц назад
The answer to Q38 is option B and not Option C
@SubtleDisastrousKaroakes
@SubtleDisastrousKaroakes Месяц назад
Yes it's B not C
@Akkishiva
@Akkishiva Месяц назад
The correct answer for the 70 is B The correct option for the primary use of LangSmith tracing is: 2. To debug issues in the language model outputs Explanation: LangSmith tracing is designed to help you: Debug Issues: It provides detailed insights into how the model processes inputs and generates outputs. This helps in identifying and troubleshooting problems such as unexpected results, performance issues, or inefficient behavior. Why Other Options Are Less Appropriate: To analyze the reasoning process of the language models: While tracing can provide insights into the model’s behavior, its primary focus is on debugging and troubleshooting rather than in-depth reasoning analysis. To generate test cases for the language models: LangSmith tracing does not directly generate test cases. Instead, it helps analyze the model’s performance when provided with test cases. To monitor the performance of the language models: While tracing can provide performance insights, its main purpose is more focused on debugging specific issues rather than broad performance monitoring. Thus, debugging issues in the language model outputs is the primary and most accurate use of LangSmith tracing.
@prakharshukla7191
@prakharshukla7191 Месяц назад
Today i have my exam in 2 hr these same questions will apear in the exam. ? is it 100% sure
@suryasundarkumar
@suryasundarkumar Месяц назад
are the questions same?
@BrunoOliveiraa2020
@BrunoOliveiraa2020 Месяц назад
Hi Guys, This Exame in ORACLE, this Supervisioned at WEBCAM? This Possible Cheat on the Exam?
@kishoreb5420
@kishoreb5420 Месяц назад
I guess somehow we can do it if you manage to hide ur phone from web cam
@SRTMLops
@SRTMLops Месяц назад
Why do not study as the others? the "gambiarra" is not the best way.
@EDUBERTUCCHI
@EDUBERTUCCHI Месяц назад
Nice video. Tks.
@pandu7820
@pandu7820 Месяц назад
Thanks for watching!
@january3515
@january3515 Месяц назад
Q 43 answer is A, not B
@bmateti
@bmateti Месяц назад
43 A is correct
@riteshmehta2292
@riteshmehta2292 Месяц назад
could you please share the pdf for it? I have sent a message on telegram but didn't get any response.
@AdityaBhuyanHub
@AdityaBhuyanHub Месяц назад
For Q-51, the answer should be A .
@pandu7820
@pandu7820 Месяц назад
No, once cross check
@pintu1111
@pintu1111 Месяц назад
Answer to Q 70 is A not D
@hitendrashingane7014
@hitendrashingane7014 Месяц назад
Que 54 - The correct answer is C
@pandu7820
@pandu7820 Месяц назад
No mmr is the technique designed to balance between diversity in the set of retrieved documents
@neerajrankireddy4168
@neerajrankireddy4168 Месяц назад
Is this working?
@SubtleDisastrousKaroakes
@SubtleDisastrousKaroakes Месяц назад
56) Which is not a category of pretrained foundational models available in the OCI Generative AI service? B) Summarization models
@pandu7820
@pandu7820 Месяц назад
@@SubtleDisastrousKaroakes no
@SuperKoffeebrown
@SuperKoffeebrown Месяц назад
It's Embedding
@get_rekt7701
@get_rekt7701 Месяц назад
Bro can you please send me link to the pdf for this? I don't have telegram. :(
@DanShdMescAbd
@DanShdMescAbd Месяц назад
If i prepare these questions can i pass the exam ??
@vasutamizhanda5184
@vasutamizhanda5184 Месяц назад
For 62 i think A is the right answer
@suneelkumar-gt4wg
@suneelkumar-gt4wg Месяц назад
@pandu, can you please send ppt or PDF.Thanks
@pandu7820
@pandu7820 Месяц назад
Msg me on telegram @technologycreator
@NehaSharma-ew4mu
@NehaSharma-ew4mu Месяц назад
Question 43: Ans A
@pandu7820
@pandu7820 Месяц назад
@@NehaSharma-ew4mu I pinned the msg that already corrected me
@bsreddy9487
@bsreddy9487 Месяц назад
Hi bro, Can you please provide ppt or pdf. Thank you
@pandu7820
@pandu7820 Месяц назад
Msg me on telegram @technologycreator
@creadortrending
@creadortrending Месяц назад
Hello! Can I please have the PDF ?
@pandu7820
@pandu7820 Месяц назад
Msg me on telegram @technologycreator
@Poojachauhan-hh2ok
@Poojachauhan-hh2ok Месяц назад
Hi can u please provide the pdf ?
@pandu7820
@pandu7820 Месяц назад
Msg me on telegram @technologycreator
@SAIVENKATARAMANAMUDA
@SAIVENKATARAMANAMUDA Месяц назад
can you provide the ppt or pdf
@pandu7820
@pandu7820 Месяц назад
Msg me on telegram @technologycreator
@kicknclick306
@kicknclick306 Месяц назад
Is it Online live Proctored exam? Am I allowed switch tab to search for answer?
@pandu7820
@pandu7820 Месяц назад
It is online live proctored and you are not allowed to switch tabs
@LolLoloilol
@LolLoloilol Месяц назад
can you provide the ppt or pdf?
@LolLoloilol
@LolLoloilol Месяц назад
@@pandu7820 done
@prakharshukla7191
@prakharshukla7191 Месяц назад
I also want pdf can you send it on mail?
@pratikgupta1240
@pratikgupta1240 Месяц назад
Will the question be same everytime?
@pandu7820
@pandu7820 Месяц назад
Mostly
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