Question 1

A company is developing an ML model to predict heart disease risk. The model uses patient data,such as age, cholesterol, blood pressure, smoking status, and exercise habits. The dataset includes atarget value that indicates whether a patient has heart disease.Which ML technique will meet these requirements?

Options :

A : Unsupervised learning

B : Supervised learning

C : Reinforcement learning

D : Semi-supervised learning

Answer: B

Question 2

Which term describes the numerical representations of real-world objects and concepts that AI and natural language processing (NLP) models use to improve understanding of textual information?

Options :

A : Embeddings

B : Tokens

C : Models

D : Binaries

Answer: A

Question 3

Which of the following options represent the CORRECT statements regarding the Amazon ML services? (Select two)

Options :

A : Amazon Transcribe is an AWS service for building conversational interfaces for applications using voice and text

B : Amazon Comprehend uses machine learning models to convert speech to text

C : Amazon Polly is used to deploy high-quality, natural-sounding human voices in dozens of languages

D : Amazon Rekognition can extract key phrases and automatically organizes a collection of text files by topic

E : Amazon Comprehend service uses machine learning to find insights and relationships in the text

Answer: C,E

Question 4

A technology consulting firm is advising a client on the use of AI to enhance their business operations, particularly through the implementation of large-scale models that can handle diverse tasks such as text generation, image recognition, and natural language understanding. The firm is evaluating Foundation Models as a potential solution and wants to clarify their capabilities, including their ability to generalize across multiple domains and perform a wide range of tasks with minimal fine-tuning.Which of the following options aptly summarizes the capabilities of Foundation Models?

Options :

A : Foundation models are limited to simple data processing tasks and cannot handle complex operations

B : Foundation models can perform a wide range of tasks across different domains by leveraging their extensive pre-training on large datasets

C : Foundation models can only perform a single task they were specifically trained for

D : Foundation models are designed to work exclusively with structured data and cannot process unstructured data like text or images

Answer: B

Question 5

What does an F1 score measure in the context of foundation model (FM) performance?

Options :

A : Model precision and recall.

B : Model speed in generating responses.

C : Financial cost of operating the model.

D : Energy efficiency of the model-s computations.

Answer: A

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