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[General] Relevant C_AIG_2412 Exam Dumps & Book C_AIG_2412 Free

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【General】 Relevant C_AIG_2412 Exam Dumps & Book C_AIG_2412 Free

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q59-Q64):NEW QUESTION # 59
Which of the following are features of the SAP AI Foundation? Note: There are 2 correct answers to this question.
  • A. Ready-to-use Al services
  • B. Al runtimes and lifecycle management
  • C. Open source Al model repository
  • D. Joule integration in SAP SuccessFactors
Answer: A,B

NEW QUESTION # 60
What must be defined in an executable to train a machine learning model using SAP AI Core? Note: There are 2 correct answers to this question.
  • A. Deployment templates for SAP AI Launchpad
  • B. Infrastructure resources such as CPUs or GPUs
  • C. User scripts to manually execute pipeline steps
  • D. Pipeline containers to be used
Answer: B,D
Explanation:
When training a machine learning model using SAP AI Core, defining an executable requires specifying certain key components to ensure the training process is efficient and effective.
1. Pipeline Containers to Be Used:
* Definitionipeline containers encapsulate the environments and dependencies necessary for each step of the machine learning workflow, including data preprocessing, model training, and evaluation.
* Specification in Executable:Within the executable, it's essential to define which pipeline containers will be utilized to ensure that each stage of the training process has the appropriate tools and libraries.

NEW QUESTION # 61
What does SAP recommend you do before you start training a machine learning model in SAP AI Core?
Note: There are 3 correct answers to this question.
  • A. Define the required infrastructure resources for training.
  • B. Configure the training pipeline using templates.
  • C. Perform manual data integration with SAP HANA.
  • D. Register the input dataset in SAP AI Core.
  • E. Configure the model deployment in SAP Al Launchpad.
Answer: A,B,D
Explanation:
Before initiating the training of a machine learning model in SAP AI Core, SAP recommends the following steps:
* Configure the training pipeline using templates:Utilize predefined templates to set up the training pipeline, ensuring consistency and efficiency in the training process.
* Define the required infrastructure resources for training:Specify the computational resources, such as CPUs or GPUs, necessary for the training job to ensure optimal performance.
* Register the input dataset in SAP AI Core:Ensure that the dataset intended for training is properly registered within SAP AI Core, facilitating seamless access during the training process.
These preparatory steps are crucial for the successful training of machine learning models within the SAP AI Core environment.

NEW QUESTION # 62
You want to assign urgency and sentiment categories to a large number of customer emails. You want to get a valid json string output for creating custom applications. You decide to develop a prompt for the same using generative Al hub.
What is the main purpose of the following code in this context?
prompt_test = """Your task is to extract and categorize messages. Here are some examples:
{{?technique_examples}}
Use the examples when extract and categorize the following message:
{{?input}}
Extract and return a json with the following keys and values:
- "urgency" as one of {{?urgency}}
- "sentiment" as one of {{?sentiment}}
"categories" list of the best matching support category tags from: {{?categories}} Your complete message should be a valid json string that can be read directly and only contains the keys mentioned in t import random random.seed(42) k = 3 examples random. sample (dev_set, k) example_template = """<example> {example_input} examples
'---'.join([example_template.format(example_input=example ["message"], example_output=json.dumps (example[ f_test = partial (send_request, prompt=prompt_test, technique_examples examples, **option_lists) response = f_test(input=mail["message"])
  • A. Train a language model from scratch
  • B. Preprocess a dataset for machine learning
  • C. Generate random examples for language model training
  • D. Evaluate the performance of a language model using few-shot learning
Answer: D

NEW QUESTION # 63
Which of the following must you do before connecting to a dataset in order to train a machine learning model in SAP Al Core?
Note: There are 2 correct answers to this question.
  • A. Grant access rights to the SAP BTP cockpit.
  • B. Provide the storage secret to access the dataset.
  • C. Store the dataset in a hyperscaler object store.
  • D. Store the dataset in the SAP HANA Vector Engine.
Answer: B,C
Explanation:
Before connecting to a dataset for training a machine learning model in SAP AI Core, the following steps are necessary:
* Store the dataset in a hyperscaler object store:Ensure that the dataset is stored in a compatible object storage service provided by a cloud hyperscaler (e.g., AWS S3, Azure Blob Storage) to facilitate seamless access during training.
* Provide the storage secret to access the dataset:Configure the necessary access credentials (storage secrets) within SAP AI Core to securely connect to and retrieve the dataset from the object store.
These steps are essential to establish a secure and efficient connection to the dataset, enabling successful model training within SAP AI Core.

NEW QUESTION # 64
......
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