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NEW QUESTION 20
A Machine Learning Specialist is using Apache Spark for pre-processing training data As part of the Spark pipeline, the Specialist wants to use Amazon SageMaker for training a model and hosting it Which of the following would the Specialist do to integrate the Spark application with SageMaker? (Select THREE )

A. Use the appropriate estimator from the SageMaker Spark Library to train a model.B. Compress the training data into a ZIP file and upload it to a pre-defined Amazon S3 bucket.C. Use the sageMakerModel. transform method to get inferences from the model hosted in SageMakerD. Convert the DataFrame object to a CSV file, and use the CSV file as input for obtaining inferences from SageMaker.E. Download the AWS SDK for the Spark environmentF. Install the SageMaker Spark library in the Spark environment.

Answer: B,C,D

 

NEW QUESTION 21
An employee found a video clip with audio on a company's social media feed. The language used in the video is Spanish. English is the employee's first language, and they do not understand Spanish. The employee wants to do a sentiment analysis.
What combination of services is the MOST efficient to accomplish the task?

A. Amazon Transcribe, Amazon Translate, and Amazon SageMaker Neural Topic Model (NTM)B. Amazon Transcribe, Amazon Translate and Amazon SageMaker BlazingTextC. Amazon Transcribe, Amazon Comprehend, and Amazon SageMaker seq2seqD. Amazon Transcribe, Amazon Translate, and Amazon Comprehend

Answer: D

Explanation:
https://aws.amazon.com/getting-started/hands-on/analyze-sentiment-comprehend/

 

NEW QUESTION 22
A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a machine learning specialist will build a binary classifier based on two features: age of account, denoted by x, and transaction month, denoted by y. The class distributions are illustrated in the provided figure. The positive class is portrayed in red, while the negative class is portrayed in black.

Which model would have the HIGHEST accuracy?

A. Single perceptron with a Tanh activation functionB. Support vector machine (SVM) with a radial basis function kernelC. Linear support vector machine (SVM)D. Decision tree

Answer: B

 

NEW QUESTION 23
An insurance company is developing a new device for vehicles that uses a camera to observe drivers' behavior and alert them when they appear distracted. The company created approximately 10,000 training images in a controlled environment that a Machine Learning Specialist will use to train and evaluate machine learning models.
During the model evaluation, the Specialist notices that the training error rate diminishes faster as the number of epochs increases and the model is not accurately inferring on the unseen test images.
Which of the following should be used to resolve this issue? (Choose two.)

A. Add L2 regularization to the model.B. Add vanishing gradient to the model.C. Perform data augmentation on the training data.D. Make the neural network architecture complex.E. Use gradient checking in the model.

Answer: A,C

Explanation:
The model must have been overfitted. Regularization helps to solve the overfitting problem in machine learning (as well as data augmentation).

 

NEW QUESTION 24
A Machine Learning Specialist needs to be able to ingest streaming data and store it in Apache Parquet files for exploration and analysis.
Which of the following services would both ingest and store this data in the correct format?

A. AWS DMSB. Amazon Kinesis Data AnalyticsC. Amazon Kinesis Data FirehoseD. Amazon Kinesis Data Streams

Answer: C

 

NEW QUESTION 25
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