A photograph showing gingerbread men being cut out with a cookie cutter to symbolize selecting a SageMaker built-in algorithm for an appropriate problem

35 Q & A for SageMaker built-in algorithms

The AWS Machine Learning – Speciality certification exam (MLS-C01) tests your abilities to select the correct answer to real life scenarios. 36% of the questions in the MLS-C01 exam will be from Domain 3. These SageMaker built-in algorithms are part of Sub-domain 3.2, Select the appropriate models for a given Machine Learning problem. Sub-domain 3.2 describes SageMaker’s 17 built-in algorithms, their features and how they can be chosen to solve a given problem. Each of the SageMaker built-in algorithms is described with the same level of detail as the exam questions in the Study Guides organised by the most significant paradigm or data processed. There are four Study Guides, as shown in this table:

Main paradigm / dataSupervisedUnsupervisedTextImages
Number of algorithms5543
This table shows the number of SageMaker built-in algorithms in each main paradigms / data processed groups.

The table below shows SageMaker built-in algorithms listed in alphabetical order with their paradigm or the data type they process.

Algorithm nameParadigm / data type processed
Blazing TextText
Deep AR ForecastingSupervised
Factorization MachinesSupervised
Image ClassificationImage
IP InsightsUnsupervised
K-MeansUnsupervised
K-Nearest Neighbor (K-NN)Supervised
Latent Dirichlet Allocation (LDA)Text
Linear LearnerSupervised
Neural Topic Model (NTM)Text
Object DetectionImage
Object2vecUnsupervised
Principal Component Analysis (PCA)Unsupervised
Random Cut Forest (RCF)Unsupervised
Semantic SegmentationImage
Sequence-to-sequenceText
XGBoostSupervised
Each link will take you to the Study Guide for that SageMaker built-in algorithm.

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Whizlabs AWS Certified Machine Learning Specialty

Practice Exams with 271 questions, Video Lectures and Hands-on Labs from Whizlabs

Whizlab’s AWS Certified Machine Learning Specialty Practice tests are designed by experts to simulate the real exam scenario. The questions are based on the exam syllabus outlined by official documentation. These practice tests are provided to the candidates to gain more confidence in exam preparation and self-evaluate them against the exam content.

Practice test content

  • Free Practice test – 15 questions
  • Practice test 1 – 65 questions
  • Practice test 2 – 65 questions
  • Practice test 3 – 65 questions
Whizlabs AWS certified machine learning course with a robot hand

Section test content

  • Core ML Concepts – 10 questions
  • Data Engineering – 11 questions
  • Exploratory Data Analysis – 13 questions
  • Modeling – 15 questions
  • Machine Learning Implementation and Operations – 12 questions

Questions

The following Questions and Answers will help you to prepare for the AWS Machine Learning – Speciality certification exam. The Questions and Answers are organized into two tests:

Choose the SageMaker built-in algorithm

For a given use, choose the most appropriate SageMaker built-in algorithms. There are 18 multiple choice questions with one or more answers.

0 votes, 0 avg
38
Created on By Michael Stainsbury

3.2 Matching algorithms to uses

Exam cram Q & A for choosing a SageMaker built-in algorithm based on what it is used for. Five questions from a test bank of 18 questions.

1 / 5

Which two SageMaker built in algorithms can be used for Topic modeling?

2 / 5

Which SageMaker built in algorithm can be used for image and multi-label classification?

3 / 5

What are the Image processing algorithms?

4 / 5

Which SageMaker built in algorithm can be used for Text Classification problems?

5 / 5

What are the SageMaker built in algorithms that can be used for Embedding?

Your score is

The average score is 58%

0%

Choose an algorithm from a list of uses

For a given SageMaker built-in algorithm choose from a list of uses appropriate for the algorithm. There are 17 multiple choice questions with one or more answers.

0 votes, 0 avg
21
Created on By Michael Stainsbury

3.2 Matching uses to algorithms

Exam cram Q & A for identifying uses for a SageMaker built-in algorithm. Five questions from a test bank of 17 questions.

1 / 5

What can the Factorization Machines algorithm do, or be used for?

2 / 5

What can the K-Nearest Neighbors algorithm do, or be used for?

3 / 5

What can the Random Cut Forest (RCF) algorithm do, or be used for?

4 / 5

What can the NTM algorithm do, or be used for?

5 / 5

What can the K-Means algorithm do, or be used for?

Your score is

The average score is 45%

0%

Choose input data for an algorithm

Please select quiz


Whizlab’s AWS Certified Machine Learning Specialty course

  • In Whizlabs AWS Machine Learning certification course, you will learn and master how to build, train, tune, and deploy Machine Learning (ML) models on the AWS platform.
  • Whizlab’s Certified AWS Machine Learning Specialty practice tests offer you a total of 200+ unique questions to get a complete idea about the real AWS Machine Learning exam.
  • Also, you get access to hands-on labs in this course. There are about 10 lab sessions that are designed to take your practical skills on AWS Machine Learning to the next level.
Whizlabs AWS certified machine learning course with a robot hand

Course content

The course has 3 resources which can be purchased seperately, or together:

  • 9 Practice tests with 271 questions
  • Video course with 65 videos
  • 9 hands on labs

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