AWS Machine Learning Specialty Exam Questions With
Complete Solutions
2 Techniques to Address Outliers in Data Correct Answers
Robust standardization : Ignore the outliers from the calculation
of the mean and standard deviation, then use the calculated
values to scale the variable.
This is called robust standardization or robust data scaling.
Logarithm transformation and Robust Standardization are the
correct techniques to address the outliers in data.
& Log transformation : The Log Transform decreases the effect
of the outliers, due to the normalization of magnitude
differences and the model become more robust.
The logarithm, x to log base 10 of x, or x to log base e of x (ln
x), or x to log base 2 of x, is a strong transformation with a
major effect on distribution shape. It is commonly used for
reducing right skewness and is often appropriate for measured
variables. It can not be applied to zero or negative values. One
unit on a logarithmic scale means a multiplication by the base of
logarithms being used.
2 ways to reduce cost of automatic hyperparameter tuning job
Correct Answers Use less concurrency while tuning : Since the
tuning process learns from each incremental step, too much
concurrency can actually hinder that learning. Use logarithmic
scales on parameter ranges: Logarithmic ranges tend to find
optimal values more quickly than linear ranges.
3 Steps to SageMaker Deployment Correct Answers 1) Create
model 2) Create HTTPS endpoint 3) Create HTTPS endpoint
config
,3 Visualizations to Spot Outliers Correct Answers 1) Box and
whisker 2) Scatter plot 3) Histogram
4 Methods for Encrypting Objects in S3 Correct Answers SSE-
S3: encrypts objects using keys managed by AWS. SSE-KMS:
Key Mgmt Service manages encryption keys (addtl security and
audit trails). SSE-C: manage your own encryption keys. Client
Side Encryption.
A Hyperparameter tuning job in SageMaker is using more time
and resources than you are willing to spend. What might be one
way to make it more efficient? Correct Answers Restrict the
search space by limiting hyperparameter ranges as much as
possible.
Accuracy Correct Answers TP + TN / TP + TN + FP + FN .
How many times the model predicted correctly over all total
preditions right + wrong.
Activation Functions Correct Answers Define the output of a
node/neuron given its input signals.
Amazon API Gateway Correct Answers A fully managed
service that makes it easy for developers to create, publish,
maintain, monitor, and secure APIs at any scale. API Gateway
can be used to present an external-facing, single point of entry
for Amazon SageMaker endpoints. API Gateway can be used to
front an Amazon SageMaker inference endpoint as (part of) a
REST API, by making use of an API Gateway feature called
mapping templates. This feature makes it possible for the REST
,API to be integrated directly with an Amazon SageMaker
runtime endpoint, thereby avoiding the use of any intermediate
compute resource (such as AWS Lambda or Amazon ECS
containers) to invoke the endpoint. The result is a solution that is
simpler, faster, and cheaper to run.
Amazon Athena Correct Answers Amazon Athena is an
interactive query service that makes it easy to analyze data in
Amazon S3
using standard SQL
serverless
pay for only the queries you run.
Amazon Augmented AI (Amazon A2I) Correct Answers
Enables you to build the workflows that are required for human
review of machine learning predictions. Amazon Textract is
directly integrated with Amazon A2I so that you can easily get
low-confidence results from Amazon Textract's
AnalyzeDocument API operation reviewed by humans.
Amazon CloudWatch API Operations Correct Answers
Amazon CloudWatch API operations sends training metrics to
CloudWatch and creates a dashboard of those metrics. Lastly,
use Amazon Simple Notification Service (Amazon SNS) to send
a notification when the model is overfitting. You can optionally
add a Lambda function to the architecture if you wish to run
some mitigation plan (e.g., stop the training when overfitting
occurs). In the scenario, Amazon SNS would suffice as we only
need to send notifications.
, Amazon CloudWatch Correct Answers You can monitor
Amazon SageMaker using Amazon CloudWatch, which collects
raw data and processes it into readable, near real-time metrics.
These statistics are kept for 15 months so that you can access
historical information and gain a better perspective on how your
web application or service is performing. To help you debug
your processing jobs, training jobs, endpoints, transform jobs,
notebook instances, and notebook instance lifecycle
configurations, anything an algorithm container, a model
container, or a notebook instance lifecycle configuration sends
to stdout or stderr is also sent to Amazon CloudWatch Logs. In
addition to debugging, you can use these for progress analysis.
You can also use Amazon CloudWatch Events to react to
different SageMaker Events.
Amazon Comprehend Correct Answers (NLP) service that uses
machine learning to find insights and relationships in a text. No
machine learning experience required.The service identifies the
language of the text; extracts key phrases, places, people,
brands, or events; understands how positive or negative the text
is; analyzes text using tokenization and parts of speech, and
automatically organizes a collection of text files by topic. You
can also use AutoML capabilities in Amazon Comprehend to
build a custom set of entities or text classification models that
are tailored uniquely to your organization's needs.
Amazon DMS Correct Answers Database Migration Service to
quickly migrate databases to AWS. Source DB remains
available during migration. Must create an EC2 instance to
perform data replication tasks between source and target DBs.
No data transformation, migration only.
Complete Solutions
2 Techniques to Address Outliers in Data Correct Answers
Robust standardization : Ignore the outliers from the calculation
of the mean and standard deviation, then use the calculated
values to scale the variable.
This is called robust standardization or robust data scaling.
Logarithm transformation and Robust Standardization are the
correct techniques to address the outliers in data.
& Log transformation : The Log Transform decreases the effect
of the outliers, due to the normalization of magnitude
differences and the model become more robust.
The logarithm, x to log base 10 of x, or x to log base e of x (ln
x), or x to log base 2 of x, is a strong transformation with a
major effect on distribution shape. It is commonly used for
reducing right skewness and is often appropriate for measured
variables. It can not be applied to zero or negative values. One
unit on a logarithmic scale means a multiplication by the base of
logarithms being used.
2 ways to reduce cost of automatic hyperparameter tuning job
Correct Answers Use less concurrency while tuning : Since the
tuning process learns from each incremental step, too much
concurrency can actually hinder that learning. Use logarithmic
scales on parameter ranges: Logarithmic ranges tend to find
optimal values more quickly than linear ranges.
3 Steps to SageMaker Deployment Correct Answers 1) Create
model 2) Create HTTPS endpoint 3) Create HTTPS endpoint
config
,3 Visualizations to Spot Outliers Correct Answers 1) Box and
whisker 2) Scatter plot 3) Histogram
4 Methods for Encrypting Objects in S3 Correct Answers SSE-
S3: encrypts objects using keys managed by AWS. SSE-KMS:
Key Mgmt Service manages encryption keys (addtl security and
audit trails). SSE-C: manage your own encryption keys. Client
Side Encryption.
A Hyperparameter tuning job in SageMaker is using more time
and resources than you are willing to spend. What might be one
way to make it more efficient? Correct Answers Restrict the
search space by limiting hyperparameter ranges as much as
possible.
Accuracy Correct Answers TP + TN / TP + TN + FP + FN .
How many times the model predicted correctly over all total
preditions right + wrong.
Activation Functions Correct Answers Define the output of a
node/neuron given its input signals.
Amazon API Gateway Correct Answers A fully managed
service that makes it easy for developers to create, publish,
maintain, monitor, and secure APIs at any scale. API Gateway
can be used to present an external-facing, single point of entry
for Amazon SageMaker endpoints. API Gateway can be used to
front an Amazon SageMaker inference endpoint as (part of) a
REST API, by making use of an API Gateway feature called
mapping templates. This feature makes it possible for the REST
,API to be integrated directly with an Amazon SageMaker
runtime endpoint, thereby avoiding the use of any intermediate
compute resource (such as AWS Lambda or Amazon ECS
containers) to invoke the endpoint. The result is a solution that is
simpler, faster, and cheaper to run.
Amazon Athena Correct Answers Amazon Athena is an
interactive query service that makes it easy to analyze data in
Amazon S3
using standard SQL
serverless
pay for only the queries you run.
Amazon Augmented AI (Amazon A2I) Correct Answers
Enables you to build the workflows that are required for human
review of machine learning predictions. Amazon Textract is
directly integrated with Amazon A2I so that you can easily get
low-confidence results from Amazon Textract's
AnalyzeDocument API operation reviewed by humans.
Amazon CloudWatch API Operations Correct Answers
Amazon CloudWatch API operations sends training metrics to
CloudWatch and creates a dashboard of those metrics. Lastly,
use Amazon Simple Notification Service (Amazon SNS) to send
a notification when the model is overfitting. You can optionally
add a Lambda function to the architecture if you wish to run
some mitigation plan (e.g., stop the training when overfitting
occurs). In the scenario, Amazon SNS would suffice as we only
need to send notifications.
, Amazon CloudWatch Correct Answers You can monitor
Amazon SageMaker using Amazon CloudWatch, which collects
raw data and processes it into readable, near real-time metrics.
These statistics are kept for 15 months so that you can access
historical information and gain a better perspective on how your
web application or service is performing. To help you debug
your processing jobs, training jobs, endpoints, transform jobs,
notebook instances, and notebook instance lifecycle
configurations, anything an algorithm container, a model
container, or a notebook instance lifecycle configuration sends
to stdout or stderr is also sent to Amazon CloudWatch Logs. In
addition to debugging, you can use these for progress analysis.
You can also use Amazon CloudWatch Events to react to
different SageMaker Events.
Amazon Comprehend Correct Answers (NLP) service that uses
machine learning to find insights and relationships in a text. No
machine learning experience required.The service identifies the
language of the text; extracts key phrases, places, people,
brands, or events; understands how positive or negative the text
is; analyzes text using tokenization and parts of speech, and
automatically organizes a collection of text files by topic. You
can also use AutoML capabilities in Amazon Comprehend to
build a custom set of entities or text classification models that
are tailored uniquely to your organization's needs.
Amazon DMS Correct Answers Database Migration Service to
quickly migrate databases to AWS. Source DB remains
available during migration. Must create an EC2 instance to
perform data replication tasks between source and target DBs.
No data transformation, migration only.
