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AWS AI Certified Practitioner Study Notes > Udemy Test 1 > Flashcards

Udemy Test 1 Flashcards

1
Q

What is a token

A

A generative AI concept used to represent words, sub words or characters that a model processes as discrete units of text

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2
Q

What is Sampling Bias?

A

It occurs when the data used to train a model does not reflect the diversity of the real world population

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3
Q

What is confirmation bias?

A

Selectively searching for or interpreting information to confirm existing beliefs

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4
Q

What is observer bias?

A

Human errors or subjectivity during data analysis or observation

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5
Q

What is measurement bias?

A

Inaccuracies in data collection

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6
Q

What is hallucination?

A

The model generates seemingly accurate information, that is incorrect

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7
Q

What is negative prompting?

A

Guiding a Gen AI model to avoid certain outputs, or behaviors when generating text

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8
Q

What is Sagemaker Clarify?

A

A tool to help explain how machine learning models make predictions

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9
Q

What is Amazon Poly?

A

Used to deploy high quality natural sounding human voices in dozens of languages

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10
Q

What is Amazon Comprehend?

A

Uses machine learning to find insights and relationships in text

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11
Q

What is knowledge bases for Amazon Bedrock?

A

You can give foundational models and Agents contextual information from your companies private data sources for RAG to deliver more relevant, accurate and customized responses

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12
Q

What is BLEU

A

A metric that is designed to evaluate the quality of text that has been machine translated by comparing with reference translations

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13
Q

What can Amazon bedrock Guardrails do?

A

It can detect confidential information in prompts or model responses

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14
Q

What is Exploritory Data Analysis (EDA)?

A

A phase of the data science process that involves examining the data through Statistical Summeries and visualizations to identify patterns, detect anomalies and form a hypothesis

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15
Q

What is Amazon Personalized?

A

A ML service that uses your data to generate product and content recommendations for your users

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16
Q

Transformer models

A

Use a self attention mechanism and implement contextual ebbeddings

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17
Q

What is Amazon Rekognition

A

A cloud based image and video service that makes it easy to add computer vision capabilities to your application

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18
Q

Key features of Amazon Sagemaker Jumpstart

A
  • Pre-trained models that are fully customizable for your use case with your data
  • You can evaluate, compare, and select foundational models quickly based on Pre-Trained quality and responsibility metrics
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19
Q

Narrowly defined use cases

A

Provide clear and specific requirements for the application, helping the research team understand exactly what the model need to accomplish

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20
Q

Amazon OpenSearch Service

A

Is designed to provide fast search capabilities and supports full text search, indexing, and scoring

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21
Q

BERT

A

A model that is used to Differentiate the contextual meaning of words when applied to different phrases

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22
Q

AWS Global Infrastructure

A
  • Each availability zone has one or more data centers
  • Each AWS region has a minimum of 3 AZ’s
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23
Q

Few Shot Prompting

A

Involves providing the model with a few examples that include user input and the correct user intent

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24
Q

Plagiarism

A

Presenting someone else’s work, ideas or creations as your own. A concern that exists around AI

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25
Q

Foundational models

A

Use self-supervised learning to create labels from input data

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26
Q

Fine Tuning a foundational model

A

Is a supervised learning process

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27
Q

Continued Pre-training

A

Uses Unlabeled data to pre-train a model

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28
Q

Fine Tuning

A

Uses labeled data to train a model

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29
Q

Testing and Deploying customized models for Bedrock

A

It is mandatory to use provisional throughput

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30
Q

Hyperparameter Tuning

A

Allows you to adjust settings such as reguklaization, learning rates, and drop out rates to enhance the models ability to generalize Local to new data

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31
Q

Asynchronous Inference

A

Allows you to process smaller payloads without requiring real-time responses by queuing requests and handling them in the background. It’s cost effective and efficient when a delay is acceptable

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32
Q

Valid use case for Gen AI

A

Create Photorealistic images from text descriptions is a valid use case

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33
Q

use MFLOW with Amazon Sagemaker:

A

To track, organize, view, analyze and compare iterative ML experimentation to gain insights and register and deploy models

34
Q

Rag approach

A

The least costly and most efficient solution for providing up to date and relevant responses

35
Q

What does Amazon Q business web application workflow use?

A
  • Retrieval augmented Generation (RAG)
  • Large Language Model (LLM)
36
Q

Approaches that are best for changing a Foundation Model(FM) into a domain specific expert

A
  • Continual Pre-Training
  • Domain Adaptive Fine Tuning
37
Q

What can Amazon Rekognition not be use for?

A

To create multilingual User Experiances

38
Q

What do you use to get more creative responses from the same prompt in Bedrock?

A

Use higher Tempature

39
Q

What is the Shared Security model for AWS

A

AWS is responsible for security of the cloud, while the user is responsible for security in the cloud

40
Q

What is the best pricing cloud option for a company that is uncertain about the time or commitment or extent of use

A

On demand pricing

41
Q

What are decision trees ?

A

Highly interpretable models that provide a clear and straightforward visualization of the decision making process

42
Q

What are Agents for Amazon Bedrock?

A

Fully managed capabilities that make it easier for developers to create Generative AI based applications that can complete complex tasks for a wide range of use cases

43
Q

What are Partial Dependable Plots(PDP)?

A

The provide a global view of a models behavior by showing how the model changes as a single feature is varied across it’s range

44
Q

What is Amazon transcribe?

A

It converts audio input into text

45
Q

What is amazon Comprehend

A

A virtual NLP (Natural Language Processing) service that uses machine learning to find insights and relationships in text

46
Q

What is Generative AI

A

It encompasses models and algorithms capable of creating new content such as text, images and audio based on patterns learned from existing data

47
Q

What is reinforcement learning?

A

It involves an agent interacting with an environment by taking actions and receiving rewards or penalties, learning to maximize cumulative rewards over time

48
Q

What is invocation logging?

A

Allows for detailed logging of all requests and responses during model invocations

49
Q

What is the default vector database for amazon bedrock

A

Opensearch serverless vector store

50
Q

Confusion matrix

A

A tool designed to evaluate the performance of classification models by displaying the number of positives, negatives as well as false positives and false negatives

51
Q

What is top P

A

The percentage of most likely candidates that a model considers for the next token

52
Q

When using top p, how do you increase the size of the pool?

A

Choose a higher value

53
Q

When using top P, how do you decrease the size of the pool

A

Choose a lower value to decrease the size of the pool and limit options to likely outputs

54
Q

What is Amazon Kendra?

A

A highly accurate and easy to use search service

55
Q

What powers Amazon Kendra?

A

Machine learning

56
Q

What is a context window?

A

It defines how much text the AI Model can process process at one time to generate good output

57
Q

What is Sagemaker model dashboard?

A

A centralized portal where you can view, search and explain all models in your account

58
Q

What is Amazon Forecast?

A

A fully managed service that uses statistical and Machine Learning Algorithms to deliver highly accurate time series forecasts

59
Q

What is Model evaluation?

A

The process of evaluating and comparing model output to determine the model that is best suited for a case

60
Q

What is Model evaluation?

A

The process of evaluating and comparing model output to determine the model that is best suited for a case

61
Q

What is model Inference?

A

The process of a model generating output from a given input

62
Q

What is Top K?

A

The number of most likely candidates that the models consider for the next token

63
Q

What is Supervised learning?

A

Algorithms that train on sample data that specifies the Algorithms input and output

64
Q

What is Linear regression?

A

Refers to supervised learning models that predict a value from a continuous scale

65
Q

What is a Neural network?

A

A more complex supervised learning technique

66
Q

What is Amazon Q developer powered by?

A

Amazon Bedrock

67
Q

How do you expose a model to a more diverse set of inputs?

A

By Augmenting Data

68
Q

What is Amazon Comprehend ?

A

A Natural Language Processing(NLP) service that uses Machine Language to uncover insights and relationships in text

69
Q

What is an AI service that provides access to foundation models via an API

A

Amazon Bedrock

70
Q

What is a service that provides guidance to help you provision your resources following AWS best practices?

A

AWS Trusted Advisor

71
Q

What is AWS trusted advisor?

A

A service that provides guidance to help you provision your resources using AWS best practices

72
Q

What is the most effective way to minimize costs associated with the use of a Gen AI model in Bedrock?

A

Reduce the number of tokens in the input

73
Q

Foundational Models

A

Serve as a broad base for various AI applications by providing generalized capabilities

74
Q

What is Amazon Sagemaker ground truth?

A

It helps you to build high quality training datasets for your Machine learning models

75
Q

What are the key components of a good prompting technique?

A
  1. Instructions
  2. Context
  3. Input Data
  4. Output indicator
76
Q

What is Amazon Q?

A

A Generative AI powered assistant that allows you to create pre-packaged Gen AI applications

77
Q

Amazon Bedrock provides what?

A

An environment to build and scale Gen AI applications using a foundation models via

78
Q

What is Transfer learning?

A

A method that allows a model to utilize the knowledge learned from one task or dataset to improve it performance on a new, but related, task

79
Q

Amazon bedrock is the easiest way to?

A

Build and scale generative AI Applications with foundation models

80
Q

What is Amazon Sagemaker Jumpstart?

A

A machine learning hub with Foundation Models, Built in Algorithms, and pre-built ML solutions that you can deploy with just a few clicks.

81
Q

What can Generative AI do?

A

It can automate the creation of new data based on existing patterns, enhancing productivity and innovation

AWS AI Certified Practitioner Study Notes (6 decks)

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