SageMaker Flashcards
(26 cards)
What is Amazon SageMaker Canvas?
Amazon SageMaker Canvas offers a no-code user interface for model creation, specifically in machine learning.
This allows users to build machine learning models without needing programming skills.
What is the purpose of Amazon SageMaker Autopilot?
Amazon SageMaker Autopilot is designed to fully automate the machine learning processing cycle.
This includes data preparation, model training, and tuning.
What features does Amazon SageMaker JumpStart provide?
Amazon SageMaker JumpStart helps users get started quickly with:
* pretrained models
* solution templates
* example notebooks
These resources facilitate a faster onboarding process for users new to machine learning.
What does Amazon SageMaker Data Wrangler simplify?
The data preparation phase for machine learning projects
How long does data preparation traditionally take?
Weeks
How long does data preparation take with SageMaker Data Wrangler?
Just minutes
What scale of data can SageMaker Data Wrangler support?
Petabyte-scale data
Does SageMaker Data Wrangler require manual coding for data preparation?
No
What is Amazon SageMaker Feature Store?
A fully managed, purpose-built service with persisted feature storage for ML models from creation through production.
Data features are the components upon which both the training of and the decisions made by ML models are based.
What is the purpose of AWS Amazon SageMaker Model Monitor?
To monitor key performance indicators of deployed models, data quality, and model drift to check the health of models in executing their assigned tasks.
It is one of the principal elements used in the AWS community for managing ML models during production.
What does Amazon SageMaker Clarify help with?
Detecting and mitigating bias in machine learning models.
What is AWS Ground Truth used for?
Labeling data accurately, improving the dataset’s overall quality.
What is Amazon SageMaker JumpStart?
A starter toolkit for machine learning projects with support for foundational models, algorithms, and end-to-end solutions.
What can be used to evaluate models once deployed in Amazon SageMaker?
SageMaker Clarify Foundation Model Evaluations (FMEval).
True or False: Bedrock focuses on a wider range of ML use cases compared to JumpStart.
False.
Fill in the blank: Bedrock focuses on _______.
generative AI.
What is Amazon SageMaker Clarify?
A tool that helps make AI models fairer and more understandable
Amazon SageMaker Clarify is designed to enhance the interpretability and fairness of machine learning models.
What do Shapley values provide insights into?
The contribution of each feature to the model’s predictions
How can Shapley values be applied in evaluating loan applications?
They can show how different features contributed to the model’s decision
List some features that Shapley values can evaluate in loan applications.
- Income level
- Credit score
- Debt-to-income ratio
- Gender
- Race
What could significant influence of gender or race in Shapley values indicate?
Potential bias in the model
What do partial dependence plots (PDPs) show?
How predictions change when a specific feature changes while keeping all other features constant
