SageMaker Built-In Algorithms Mastery

1. Which SageMaker algorithm performs dimensionality reduction using principal component analysis?

Principal Component Analysis (PCA)

Factorization Machines

K-Means

Random Cut Forest

2. Which SageMaker built-in algorithm requires the target variable to be in the first column of CSV input?

K-Means

Linear Learner and XGBoost

Factorization Machines

Principal Component Analysis

3. The SageMaker Random Cut Forest algorithm is most commonly used for which application?

Supervised classification

Real-time anomaly detection in streaming data

Image segmentation

Natural language processing

4. What is the primary input requirement for SageMaker's Factorization Machines algorithm?

Dense numerical vectors only

Sparse or dense vectors with categorical features

Images in standard formats

Time series sequences

5. Which SageMaker algorithm supports automatic model tuning for hyperparameter optimization?

Only Linear Learner

Only XGBoost

Most built-in algorithms including XGBoost and Linear Learner

No built-in algorithms support it

6. The SageMaker Semantic Segmentation algorithm outputs predictions in which format?

CSV with pixel labels

PNG image with class indices

JSON annotations

RecordIO format

7. What does the 'num_classes' parameter specify in SageMaker's Image Classification algorithm?

Number of training epochs

Number of output classification categories

Number of layers in the network

Batch size for training

8. Which hyperparameter in SageMaker's XGBoost algorithm controls the learning rate?

Eta

Max_depth

Num_round

Objective

9. The SageMaker Sequence-to-Sequence (Seq2Seq) algorithm is best used for which task?

Image classification

Machine translation and text summarization

Clustering only

Anomaly detection

10. What is the recommended input format for SageMaker's Neural Topic Model?

Images in PNG format

Bag-of-words format or sparse vectors

Time series data only

Raw text documents

11. Which SageMaker built-in algorithm is designed for binary and multiclass classification problems using gradient boosting?

XGBoost

Linear Learner

K-Means

Factorization Machines

12. The SageMaker IP Insights algorithm is designed to detect what type of anomaly?

Image pixel anomalies

Unusual IP address patterns and behavior

Text sentiment shifts

Numerical outliers

13. Which algorithm in SageMaker is used for time series forecasting with automatic seasonality detection?

DeepAR+

Seq2Seq

Principal Component Analysis

Neural Topic Model

14. What is the primary advantage of using SageMaker's Object Detection algorithm?

It requires minimal preprocessing

It uses MXNet and supports transfer learning

It only works with grayscale images

It eliminates the need for labeled data

15. The SageMaker BlazingText algorithm is optimized for which NLP task?

Machine translation

Named entity recognition

Text classification and word embeddings

Sentiment analysis only

16. Which SageMaker built-in algorithm performs unsupervised anomaly detection using isolation forests?

Random Cut Forest

IP Insights

Semantic Segmentation

Object Detection

17. What is the output format of SageMaker's Image Classification algorithm predictions?

JSON with class labels

RecordIO-protobuf format

CSV with probabilities

MXNet model format

18. The SageMaker K-Means algorithm requires input data in what format?

CSV only

RecordIO-protobuf or CSV

JSON only

Parquet only

19. Which algorithm in SageMaker is best suited for recommendation systems and sparse data?

K-Means

Image Classification

Factorization Machines

Random Cut Forest

20. What is the primary use case for the SageMaker Linear Learner algorithm?

Unsupervised clustering

Regression and binary/multiclass classification

Dimensionality reduction

Time series forecasting

AWS ML Specialty SageMaker Built In Algorithms Quiz

1. Which SageMaker algorithm performs dimensionality reduction using principal component analysis?

2.

What first name or nickname would you like us to use?

2. Which SageMaker built-in algorithm requires the target variable to be in the first column of CSV input?

3. The SageMaker Random Cut Forest algorithm is most commonly used for which application?

4. What is the primary input requirement for SageMaker's Factorization Machines algorithm?

5. Which SageMaker algorithm supports automatic model tuning for hyperparameter optimization?

6. The SageMaker Semantic Segmentation algorithm outputs predictions in which format?

7. What does the 'num_classes' parameter specify in SageMaker's Image Classification algorithm?

8. Which hyperparameter in SageMaker's XGBoost algorithm controls the learning rate?

9. The SageMaker Sequence-to-Sequence (Seq2Seq) algorithm is best used for which task?

10. What is the recommended input format for SageMaker's Neural Topic Model?

11. Which SageMaker built-in algorithm is designed for binary and multiclass classification problems using gradient boosting?

12. The SageMaker IP Insights algorithm is designed to detect what type of anomaly?

13. Which algorithm in SageMaker is used for time series forecasting with automatic seasonality detection?

14. What is the primary advantage of using SageMaker's Object Detection algorithm?

15. The SageMaker BlazingText algorithm is optimized for which NLP task?

16. Which SageMaker built-in algorithm performs unsupervised anomaly detection using isolation forests?

17. What is the output format of SageMaker's Image Classification algorithm predictions?

18. The SageMaker K-Means algorithm requires input data in what format?

19. Which algorithm in SageMaker is best suited for recommendation systems and sparse data?

20. What is the primary use case for the SageMaker Linear Learner algorithm?