This page was exported from Actual Test Materials [ http://blog.actualtests4sure.com ] Export date:Fri Nov 15 20:23:07 2024 / +0000 GMT ___________________________________________________ Title: Latest [Dec 28, 2023] Professional-Machine-Learning-Engineer Exam Questions – Valid Professional-Machine-Learning-Engineer Dumps Pdf [Q40-Q57] --------------------------------------------------- Latest [Dec 28, 2023] Professional-Machine-Learning-Engineer Exam Questions – Valid Professional-Machine-Learning-Engineer Dumps Pdf Professional-Machine-Learning-Engineer Practice Test Questions Answers Updated 150 Questions Google Professional Machine Learning Engineer certification is highly valued in the industry and is recognized as a benchmark of excellence in the field of machine learning. Achieving this certification demonstrates that an individual has the skills and knowledge required to design and implement machine learning solutions at scale using Google Cloud technologies. Google Professional Machine Learning Engineer certification can help individuals advance their careers and open up new opportunities in the field of machine learning.   NO.40 A Data Science team within a large company uses Amazon SageMaker notebooks to access data stored in Amazon S3 buckets. The IT Security team is concerned that internet-enabled notebook instances create a security vulnerability where malicious code running on the instances could compromise data privacy. The company mandates that all instances stay within a secured VPC with no internet access, and data communication traffic must stay within the AWS network.How should the Data Science team configure the notebook instance placement to meet these requirements?  Associate the Amazon SageMaker notebook with a private subnet in a VPC. Place the Amazon SageMaker endpoint and S3 buckets within the same VPC.  Associate the Amazon SageMaker notebook with a private subnet in a VPC. Use IAM policies to grant access to Amazon S3 and Amazon SageMaker.  Associate the Amazon SageMaker notebook with a private subnet in a VPC. Ensure the VPC has S3 VPC endpoints and Amazon SageMaker VPC endpoints attached to it.  Associate the Amazon SageMaker notebook with a private subnet in a VPC. Ensure the VPC has a NAT gateway and an associated security group allowing only outbound connections to Amazon S3 and Amazon SageMaker. NO.41 A monitoring service generates 1 TB of scale metrics record data every minute. A Research team performs queries on this data using Amazon Athena. The queries run slowly due to the large volume of data, and the team requires better performance.How should the records be stored in Amazon S3 to improve query performance?  CSV files  Parquet files  Compressed JSON  RecordIO NO.42 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?  Amazon Transcribe, Amazon Translate, and Amazon Comprehend  Amazon Transcribe, Amazon Comprehend, and Amazon SageMaker seq2seq  Amazon Transcribe, Amazon Translate, and Amazon SageMaker Neural Topic Model (NTM)  Amazon Transcribe, Amazon Translate and Amazon SageMaker BlazingText NO.43 Your team is working on an NLP research project to predict political affiliation of authors based on articles they have written. You have a large training dataset that is structured like this:A)B)C)D)  Option A  Option B  Option C  Option D If we just put inside the Training set , Validation set and Test set , randomly Text, Paragraph or sentences the model will have the ability to learn specific qualities about The Author’s use of language beyond just his own articles. Therefore the model will mixed up different opinions. Rather if we divided things up a the author level, so that given authors were only on the training data, or only in the test data or only in the validation data. The model will find more difficult to get a high accuracy on the test validation (What is correct and have more sense!). Because it will need to really focus in author by author articles rather than get a single political affiliation based on a bunch of mixed articles from different authors. https://developers.google.com/machine-learning/crash-course/18th-century-literature For example, suppose you are training a model with purchase data from a number of stores. You know, however, that the model will be used primarily to make predictions for stores that are not in the training data. To ensure that the model can generalize to unseen stores, you should segregate your data sets by stores. In other words, your test set should include only stores different from the evaluation set, and the evaluation set should include only stores different from the training set. https://cloud.google.com/automl-tables/docs/prepare#ml-useNO.44 You are working on a Neural Network-based project. The dataset provided to you has columns with different ranges. While preparing the data for model training, you discover that gradient optimization is having difficulty moving weights to a good solution. What should you do?  Use feature construction to combine the strongest features.  Use the representation transformation (normalization) technique.  Improve the data cleaning step by removing features with missing values.  Change the partitioning step to reduce the dimension of the test set and have a larger training set. NO.45 You have been asked to develop an input pipeline for an ML training model that processes images from disparate sources at a low latency. You discover that your input data does not fit in memory. How should you create a dataset following Google-recommended best practices?  Create a tf.data.Dataset.prefetch transformation  Convert the images to tf .Tensor Objects, and then run Dataset. from_tensor_slices{).  Convert the images to tf .Tensor Objects, and then run tf. data. Dataset. from_tensors ().  Convert the images Into TFRecords, store the images in Cloud Storage, and then use the tf. data API to read the images for training NO.46 You have trained a deep neural network model on Google Cloud. The model has low loss on the training data, but is performing worse on the validation dat a. You want the model to be resilient to overfitting. Which strategy should you use when retraining the model?  Apply a dropout parameter of 0 2, and decrease the learning rate by a factor of 10  Apply a 12 regularization parameter of 0.4, and decrease the learning rate by a factor of 10.  Run a hyperparameter tuning job on Al Platform to optimize for the L2 regularization and dropout parameters  Run a hyperparameter tuning job on Al Platform to optimize for the learning rate, and increase the number of neurons by a factor of 2. NO.47 A company ingests machine learning (ML) data from web advertising clicks into an Amazon S3 data lake. Click data is added to an Amazon Kinesis data stream by using the Kinesis Producer Library (KPL). The data is loaded into the S3 data lake from the data stream by using an Amazon Kinesis Data Firehose delivery stream.As the data volume increases, an ML specialist notices that the rate of data ingested into Amazon S3 is relatively constant. There also is an increasing backlog of data for Kinesis Data Streams and Kinesis Data Firehose to ingest.Which next step is MOST likely to improve the data ingestion rate into Amazon S3?  Increase the number of S3 prefixes for the delivery stream to write to.  Decrease the retention period for the data stream.  Increase the number of shards for the data stream.  Add more consumers using the Kinesis Client Library (KCL). Explanation/Reference:NO.48 You need to analyze user activity data from your company’s mobile applications. Your team will use BigQuery for data analysis, transformation, and experimentation with ML algorithms. You need to ensure real-time ingestion of the user activity data into BigQuery. What should you do?  Configure Pub/Sub to stream the data into BigQuery.  Run an Apache Spark streaming job on Dataproc to ingest the data into BigQuery.  Run a Dataflow streaming job to ingest the data into BigQuery.  Configure Pub/Sub and a Dataflow streaming job to ingest the data into BigQuery, Pub/Sub is a messaging service that can be used to stream data into BigQuery in real-time. Configuring Pub/Sub to stream the user activity data into BigQuery would ensure real-time ingestion of the data. Source: Google CloudNO.49 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?  Use a built-in model available on Al Platform Training  Build your custom container to run jobs on Al Platform Training  Build your custom containers to run distributed training jobs on Al Platform Training  Reconfigure your code to a ML framework with dependencies that are supported by Al Platform Training NO.50 A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine Learning Specialist would like to build a binary classifier based on two features: age of account and transaction month. The class distribution for these features is illustrated in the figure provided.Based on this information, which model would have the HIGHEST accuracy?  Long short-term memory (LSTM) model with scaled exponential linear unit (SELU)  Logistic regression  Support vector machine (SVM) with non-linear kernel  Single perceptron with tanh activation function NO.51 You work for an online publisher that delivers news articles to over 50 million readers. You have built an AI model that recommends content for the company’s weekly newsletter. A recommendation is considered successful if the article is opened within two days of the newsletter’s published date and the user remains on the page for at least one minute.All the information needed to compute the success metric is available in BigQuery and is updated hourly. The model is trained on eight weeks of data, on average its performance degrades below the acceptable baseline after five weeks, and training time is 12 hours. You want to ensure that the model’s performance is above the acceptable baseline while minimizing cost. How should you monitor the model to determine when retraining is necessary?  Use Vertex AI Model Monitoring to detect skew of the input features with a sample rate of 100% and a monitoring frequency of two days.  Schedule a cron job in Cloud Tasks to retrain the model every week before the newsletter is created.  Schedule a weekly query in BigQuery to compute the success metric.  Schedule a daily Dataflow job in Cloud Composer to compute the success metric. NO.52 Given the following confusion matrix for a movie classification model, what is the true class frequency for Romance and the predicted class frequency for Adventure?  The true class frequency for Romance is 77.56% and the predicted class frequency for Adventure is20.85%  The true class frequency for Romance is 57.92% and the predicted class frequency for Adventure is13.12%  The true class frequency for Romance is 0.78 and the predicted class frequency for Adventure is (0.47-0.32)  The true class frequency for Romance is 77.56% * 0.78 and the predicted class frequency for Adventure is20.85%*0.32 NO.53 You need to design a customized deep neural network in Keras that will predict customer purchases based on their purchase history. You want to explore model performance using multiple model architectures, store training data, and be able to compare the evaluation metrics in the same dashboard. What should you do?  Create multiple models using AutoML Tables  Automate multiple training runs using Cloud Composer  Run multiple training jobs on Al Platform with similar job names  Create an experiment in Kubeflow Pipelines to organize multiple runs https://www.kubeflow.org/docs/components/pipelines/concepts/experiment/ https://www.kubeflow.org/docs/components/pipelines/concepts/run/NO.54 A real estate company wants to create a machine learning model for predicting housing prices based on a historical dataset. The dataset contains 32 features.Which model will meet the business requirement?  Logistic regression  Linear regression  K-means  Principal component analysis (PCA) NO.55 You work for an online travel agency that also sells advertising placements on its website to other companies.You have been asked to predict the most relevant web banner that a user should see next. Security is important to your company. The model latency requirements are 300ms@p99, the inventory is thousands of web banners, and your exploratory analysis has shown that navigation context is a good predictor. You want to Implement the simplest solution. How should you configure the prediction pipeline?  Embed the client on the website, and then deploy the model on AI Platform Prediction.  Embed the client on the website, deploy the gateway on App Engine, and then deploy the model on AI Platform Prediction.  Embed the client on the website, deploy the gateway on App Engine, deploy the database on Cloud Bigtable for writing and for reading the user’s navigation context, and then deploy the model on AI Platform Prediction.  Embed the client on the website, deploy the gateway on App Engine, deploy the database on Memorystore for writing and for reading the user’s navigation context, and then deploy the model on Google Kubernetes Engine. https://medium.com/google-cloud/secure-cloud-run-cloud-functions-and-app-engine-with-api-key-73c57bededd1NO.56 You are an ML engineer at a regulated insurance company. You are asked to develop an insurance approval model that accepts or rejects insurance applications from potential customers. What factors should you consider before building the model?  Redaction, reproducibility, and explainability  Traceability, reproducibility, and explainability  Federated learning, reproducibility, and explainability  Differential privacy federated learning, and explainability https://www.oecd.org/finance/Impact-Big-Data-AI-in-the-Insurance-Sector.pdfhttps://medium.com/artefact-engineering-and-data-science/including-ethics-best-practices-in-your-data-science-project-from-day-one-c15b26c2bf99NO.57 A Machine Learning Specialist uploads a dataset to an Amazon S3 bucket protected with server-side encryption using AWS KMS.How should the ML Specialist define the Amazon SageMaker notebook instance so it can read the same dataset from Amazon S3?  Define security group(s) to allow all HTTP inbound/outbound traffic and assign those security group(s) to the Amazon SageMaker notebook instance.  Сonfigure the Amazon SageMaker notebook instance to have access to the VPC. Grant permission in the KMS key policy to the notebook’s KMS role.  Assign an IAM role to the Amazon SageMaker notebook with S3 read access to the dataset. Grant permission in the KMS key policy to that role.  Assign the same KMS key used to encrypt data in Amazon S3 to the Amazon SageMaker notebook instance. Explanation/Reference: https://docs.aws.amazon.com/sagemaker/latest/dg/encryption-at-rest.html Loading … How much Professional Machine Learning Engineer - Google Cost The cost of the Professional Machine Learning Engineer - Google is $200. For more information related to exam price, please visit the official website Google Website as the cost of exams may be subjected to vary county-wise. Google Professional Machine Learning Engineer certification is highly regarded in the industry and is recognized as a benchmark for machine learning expertise. It is an ideal certification for professionals who are looking to enhance their career prospects and advance their skills in machine learning. Google Professional Machine Learning Engineer certification demonstrates that the candidate has the necessary skills to design and implement machine learning solutions that meet the requirements of modern businesses.   Professional-Machine-Learning-Engineer dumps Sure Practice with 150 Questions: https://www.actualtests4sure.com/Professional-Machine-Learning-Engineer-test-questions.html --------------------------------------------------- Images: https://blog.actualtests4sure.com/wp-content/plugins/watu/loading.gif https://blog.actualtests4sure.com/wp-content/plugins/watu/loading.gif --------------------------------------------------- --------------------------------------------------- Post date: 2023-12-28 13:39:27 Post date GMT: 2023-12-28 13:39:27 Post modified date: 2023-12-28 13:39:27 Post modified date GMT: 2023-12-28 13:39:27