Professional-Machine-Learning-Engineer Actual Questions Answers PDF 100% Cover Real Exam Questions
Professional-Machine-Learning-Engineer Exam questions and answers
What is the duration, language, and format of Professional Machine Learning Engineer - Google
- Type of Questions: Multiple choice (MCQs), multiple answers
- Duration of Exam: 120 minutes
- No negative marking for wrong answers
- Language of Exam: English, Japanese, Korean
Difficulty in Writing Professional Machine Learning Engineer - Google
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NEW QUESTION 18
A credit card company wants to build a credit scoring model to help predict whether a new credit card applicant will default on a credit card payment. The company has collected data from a large number of sources with thousands of raw attributes. Early experiments to train a classification model revealed that many attributes are highly correlated, the large number of features slows down the training speed significantly, and that there are some overfitting issues.
The Data Scientist on this project would like to speed up the model training time without losing a lot of information from the original dataset.
Which feature engineering technique should the Data Scientist use to meet the objectives?
- A. Use an autoencoder or principal component analysis (PCA) to replace original features with new features
- B. Run self-correlation on all features and remove highly correlated features
- C. Normalize all numerical values to be between 0 and 1
- D. Cluster raw data using k-means and use sample data from each cluster to build a new dataset
Answer: C
NEW QUESTION 19
You recently designed and built a custom neural network that uses critical dependencies specific to your organization's framework. You need to train the model using a managed training service on Google Cloud. However, the ML framework and related dependencies are not supported by Al Platform Training. Also, both your model and your data are too large to fit in memory on a single machine. Your ML framework of choice uses the scheduler, workers, and servers distribution structure. What should you do?
- A. Build your custom container to run jobs on Al Platform Training
- B. Use a built-in model available on Al Platform Training
- C. Build your custom containers to run distributed training jobs on Al Platform Training
- D. Reconfigure your code to a ML framework with dependencies that are supported by Al Platform Training
Answer: C
NEW QUESTION 20
A Data Scientist wants to gain real-time insights into a data stream of GZIP files.
Which solution would allow the use of SQL to query the stream with the LEAST latency?
- A. Amazon Kinesis Data Firehose to transform the data and put it into an Amazon S3 bucket.
- B. An Amazon Kinesis Client Library to transform the data and save it to an Amazon ES cluster.
- C. Amazon Kinesis Data Analytics with an AWS Lambda function to transform the data.
- D. AWS Glue with a custom ETL script to transform the data.
Answer: C
Explanation:
Explanation/Reference: https://aws.amazon.com/big-data/real-time-analytics-featured-partners/
NEW QUESTION 21
You are developing ML models with Al Platform for image segmentation on CT scans. You frequently update your model architectures based on the newest available research papers, and have to rerun training on the same dataset to benchmark their performance. You want to minimize computation costs and manual intervention while having version control for your code. What should you do?
- A. Use the gcloud command-line tool to submit training jobs on Al Platform when you update your code
- B. Create an automated workflow in Cloud Composer that runs daily and looks for changes in code in Cloud Storage using a sensor.
- C. Use Cloud Build linked with Cloud Source Repositories to trigger retraining when new code is pushed to the repository
- D. Use Cloud Functions to identify changes to your code in Cloud Storage and trigger a retraining job
Answer: A
NEW QUESTION 22
A Machine Learning Specialist is training a model to identify the make and model of vehicles in images. The Specialist wants to use transfer learning and an existing model trained on images of general objects. The Specialist collated a large custom dataset of pictures containing different vehicle makes and models.
What should the Specialist do to initialize the model to re-train it with the custom data?
- A. Initialize the model with pre-trained weights in all layers including the last fully connected layer.
- B. Initialize the model with random weights in all layers including the last fully connected layer.
- C. Initialize the model with random weights in all layers and replace the last fully connected layer.
- D. Initialize the model with pre-trained weights in all layers and replace the last fully connected layer.
Answer: D
NEW QUESTION 23
You are designing an ML recommendation model for shoppers on your company's ecommerce website. You will use Recommendations Al to build, test, and deploy your system. How should you develop recommendations that increase revenue while following best practices?
- A. Use the "Frequently Bought Together' recommendation type to increase the shopping cart size for each order.
- B. Import your user events and then your product catalog to make sure you have the highest quality event stream
- C. Use the "Other Products You May Like" recommendation type to increase the click-through rate
- D. Because it will take time to collect and record product data, use placeholder values for the product catalog to test the viability of the model.
Answer: A
Explanation:
Frequently bought together' recommendations aim to up-sell and cross-sell customers by providing product.
NEW QUESTION 24
Your organization's call center has asked you to develop a model that analyzes customer sentiments in each call. The call center receives over one million calls daily, and data is stored in Cloud Storage. The data collected must not leave the region in which the call originated, and no Personally Identifiable Information (Pll) can be stored or analyzed. The data science team has a third-party tool for visualization and access which requires a SQL ANSI-2011 compliant interface. You need to select components for data processing and for analytics. How should the data pipeline be designed?
- A. 1 = Pub/Sub, 2 = Datastore
- B. 1 = Cloud Function, 2 = Cloud SQL
- C. 1 = Dataflow, 2 = Cloud SQL
- D. 1 = Dataflow, 2 = BigQuery
Answer: A
NEW QUESTION 25
You are designing an ML recommendation model for shoppers on your company's ecommerce website. You will use Recommendations Al to build, test, and deploy your system. How should you develop recommendations that increase revenue while following best practices?
- A. Import your user events and then your product catalog to make sure you have the highest quality event stream
- B. Use the "Other Products You May Like" recommendation type to increase the click-through rate
- C. Because it will take time to collect and record product data, use placeholder values for the product catalog to test the viability of the model.
- D. Use the "Frequently Bought Together' recommendation type to increase the shopping cart size for each order.
Answer: A
NEW QUESTION 26
A company's Machine Learning Specialist needs to improve the training speed of a time-series forecasting model using TensorFlow. The training is currently implemented on a single-GPU machine and takes approximately 23 hours to complete. The training needs to be run daily.
The model accuracy is acceptable, but the company anticipates a continuous increase in the size of the training data and a need to update the model on an hourly, rather than a daily, basis. The company also wants to minimize coding effort and infrastructure changes.
What should the Machine Learning Specialist do to the training solution to allow it to scale for future demand?
- A. Move the training to Amazon EMR and distribute the workload to as many machines as needed to achieve the business goals.
- B. Change the TensorFlow code to implement a Horovod distributed framework supported by Amazon SageMaker. Parallelize the training to as many machines as needed to achieve the business goals.
- C. Do not change the TensorFlow code. Change the machine to one with a more powerful GPU to speed up the training.
- D. Switch to using a built-in AWS SageMaker DeepAR model. Parallelize the training to as many machines as needed to achieve the business goals.
Answer: B
NEW QUESTION 27
A company is setting up an Amazon SageMaker environment. The corporate data security policy does not allow communication over the internet.
How can the company enable the Amazon SageMaker service without enabling direct internet access to Amazon SageMaker notebook instances?
- A. Create Amazon SageMaker VPC interface endpoints within the corporate VPC.
- B. Route Amazon SageMaker traffic through an on-premises network.
- C. Create a NAT gateway within the corporate VPC.
- D. Create VPC peering with Amazon VPC hosting Amazon SageMaker.
Answer: C
Explanation:
Explanation/Reference: https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-dg.pdf (46)
NEW QUESTION 28
A Machine Learning Specialist is packaging a custom ResNet model into a Docker container so the company can leverage Amazon SageMaker for training. The Specialist is using Amazon EC2 P3 instances to train the model and needs to properly configure the Docker container to leverage the NVIDIA GPUs.
What does the Specialist need to do?
- A. Build the Docker container to be NVIDIA-Docker compatible.
- B. Set the GPU flag in the Amazon SageMaker CreateTrainingJob request body.
- C. Organize the Docker container's file structure to execute on GPU instances.
- D. Bundle the NVIDIA drivers with the Docker image.
Answer: D
NEW QUESTION 29
You are training an LSTM-based model on Al Platform to summarize text using the following job submission script:
You want to ensure that training time is minimized without significantly compromising the accuracy of your model. What should you do?
- A. Modify the 'learning rate' parameter
- B. Modify the batch size' parameter
- C. Modify the 'epochs' parameter
- D. Modify the 'scale-tier' parameter
Answer: B
NEW QUESTION 30
A Machine Learning Specialist is designing a system for improving sales for a company. The objective is to use the large amount of information the company has on users' behavior and product preferences to predict which products users would like based on the users' similarity to other users.
What should the Specialist do to meet this objective?
- A. Build a model-based filtering recommendation engine with Apache Spark ML on Amazon EMR
- B. Build a combinative filtering recommendation engine with Apache Spark ML on Amazon EMR
- C. Build a collaborative filtering recommendation engine with Apache Spark ML on Amazon EMR.
- D. Build a content-based filtering recommendation engine with Apache Spark ML on Amazon EMR
Answer: C
Explanation:
Many developers want to implement the famous Amazon model that was used to power the "People who bought this also bought these items" feature on Amazon.com. This model is based on a method called Collaborative Filtering. It takes items such as movies, books, and products that were rated highly by a set of users and recommending them to other users who also gave them high ratings. This method works well in domains where explicit ratings or implicit user actions can be gathered and analyzed.
Reference: https://aws.amazon.com/blogs/big-data/building-a-recommendation-engine-with-spark-ml-on-amazon-emr-using-zeppelin/
NEW QUESTION 31
A data scientist has developed a machine learning translation model for English to Japanese by using Amazon SageMaker's built-in seq2seq algorithm with 500,000 aligned sentence pairs. While testing with sample sentences, the data scientist finds that the translation quality is reasonable for an example as short as five words. However, the quality becomes unacceptable if the sentence is 100 words long.
Which action will resolve the problem?
- A. Change preprocessing to use n-grams.
- B. Adjust hyperparameters related to the attention mechanism.
- C. Choose a different weight initialization type.
- D. Add more nodes to the recurrent neural network (RNN) than the largest sentence's word count.
Answer: D
NEW QUESTION 32
A financial services company is building a robust serverless data lake on Amazon S3. The data lake should be flexible and meet the following requirements:
* Support querying old and new data on Amazon S3 through Amazon Athena and Amazon Redshift Spectrum.
* Support event-driven ETL pipelines
* Provide a quick and easy way to understand metadata
Which approach meets these requirements?
- A. Use an AWS Glue crawler to crawl S3 data, an AWS Lambda function to trigger an AWS Batch job, and an external Apache Hive metastore to search and discover metadata.
- B. Use an AWS Glue crawler to crawl S3 data, an Amazon CloudWatch alarm to trigger an AWS Batch job, and an AWS Glue Data Catalog to search and discover metadata.
- C. Use an AWS Glue crawler to crawl S3 data, an AWS Lambda function to trigger an AWS Glue ETL job, and an AWS Glue Data catalog to search and discover metadata.
- D. Use an AWS Glue crawler to crawl S3 data, an Amazon CloudWatch alarm to trigger an AWS Glue ETL job, and an external Apache Hive metastore to search and discover metadata.
Answer: A
NEW QUESTION 33
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How to book the Professional Machine Learning Engineer - Google
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- Step 1: Go to the Google Official Site
- Step 2: Read the instruction carefully
- Step 3: Follow the given steps
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