GCP Professional machine learning engineer practice test.

Step into the world of a Professional Machine Learning Engineer. With Google Cloud tech as your ally, you’ll master vast datasets and create impactful models. Collaboration is key as you ensure fairness and efficiency in every project. From architecture to deployment, your expertise shines, making ML accessible to all.

Curious to test your knowledge? Take our quiz and get well-explained answers to deepen your understanding. Join us and shape a future where intelligence knows no bounds.

Welcome to your professionalmachinelearningengineer

Q1.A company that provides an online platform for employers to post open positions is building a machine learning model to predict the expected salary for a particular job posting. The team working on the model is in the exploratory phase and plans to implement a deep neural network (DNN) using TensorFlow for their machine learning algorithm. The training data set includes about 100,000 examples. The team needs to choose the appropriate hardware and platform for training the model while balancing performance and cost. Which of the following Google AI services and configurations should the team choose for this project?

Q2.A team of machine learning engineers is working on a project to build a CI/CD automation pipeline for a model that serves online predictions to a mobile application. New training data is available in a Cloud Storage bucket anywhere from every 14 to 28 days. The team is using Kubeflow to implement the training pipeline and needs to decide how often they should trigger a new training job. Which of the following strategies should the team use to trigger the training pipeline?

Q3.You recently joined a start-up that developed a mobile application to allow users to upload / share short videos. As part of the machine learning engineering team, you are working on a solution to moderate and analyze the uploaded videos for filtering out inappropriate or misinformative content. How would you design the solution to test the results with less time and effort?

Q4.You are asked to develop a solution to optimize the drop-off routes for after school buses. The students use a drop-off schedule application to confirm their drop-off location ahead of time. What’s your best approach to develop the solution?

Q5.What are distinct ways to create a dataset?

Q6.Your team has used Google’s Vertex AI Platform to train a product recommendation model. The product catalog data changes monthly and the user activity data updates daily. You need to develop a testing strategy to make sure the update from an older version of the model to a newer one is as smooth as possible and without the need to provision any new infrastructure manually. How do you deploy the model on Vertex AI Platform?

Q7.A team of data analysts at a human resources consulting firm is building a machine learning model to predict the number of days it will take to fill a job opening the company manages for its customers. The team has structured data for its training data set, but does not have a lot of experience choosing machine learning algorithms. Which of the following Google services should the team use to build this machine learning model?

Q8.You are using a Google AI Platform Notebook to develop a new machine learning model. Your dataset is in BigQuery, and you plan to write some preprocessing code to prepare the data using Python before running your training experiments. You need to decide the best way to load the data. Which of the following approaches should you use to load your data from BigQuery into your notebook?

Q9.Which of the following statements is not a feature of Analytics Hub?

Q10.Your company has developed a tabular classification model using AutoML. You have been asked by senior management to explain how the model works. You need to select a feature attribution method to help with the model explanation. Which method should you choose?

Q11.The learning rate is a hyperparameter that controls how much to change the model in response to the estimated error each time the model weights are updated. Choosing the learning rate is challenging. What can happen if the value is too large?

Q12.You are helping to develop a call center solution using Google’s CCAI (Contact Center AI). The number of human agents is very limited. You have received phone audio files from the last 3 years and were asked to design a solution to reduce the workload for the human agents, but still help the customers with questions and queries as soon as possible. How do you design the lowest effort solution that both fulfills the requirement and is quickest to market?

Q13.A team of data analysts at a company that manufactures agricultural equipment is working on a project to build a machine learning model to predict the likelihood of a component failure based on the past maintenance history for a given product. The team is familiar with SQL but does not have extensive experience with programming languages like Python or Java. The team is looking for the appropriate Google Cloud services to help prepare the training data and train the machine learning model. Which set of Google Cloud services should the team choose for this project?

Q14.You are training a machine learning model to predict the starting salary for recent graduates from various degree programs throughout the country using a deep neural network (DNN). After doing some initial data analysis on the training data set, you notice that one numeric feature is distributed relatively uniformly but contains a few extreme outliers. You are concerned that this feature could affect your model's performance and stability and want to take steps to avoid this. What can you do to ensure this feature does not negatively impact the training stability and model performance?

Q15.Model complexity often refers to the number of features or terms included in a given predictive model. What happens when the complexity of the model increases?

Q16.Your team is preparing a data set to train a new machine learning model. A junior data analyst is responsible for cleaning up and analyzing the dataset before moving into BigQuery and does not have much coding experience. You are looking for a service that would allow the analyst to visually inspect the data, identify problems, and quickly transform the data without writing code. You would also like the output of this process to be something that is easily repeatable. Which of these Google Cloud services should you choose for this data preparation step?

Q17.Which of the following algorithms is useful, if you want to specify a quantity of trials that is greater than the number of points in the feasible space?

Q18.You are working with a recruiting company to develop a ML model for filtering applicants’ resumes automatically. The goal is to select the right applicant to interview by matching applicant skills and experience. After the model is deployed and used for a while, the recruiters found that all the applicants selected for IT jobs are male and White or Asian. You are asked to make changes to the model to make sure that all applicants are selected regardless of gender and race. What is the approach to take for improving the model?

Q19.Your team is building an image classification model to detect motor vehicles in images using Google AI Platform training. You are using TensorFlow to build the model, and for training, you use the BASIC_TPU scale tier, which includes a standard master virtual machine and a worker Cloud TPU (Tensor Processing Units) with eight TPU v2 cores. For the first training run, you set the batch size to 10 and the number of iterations per loop to 500. The training time is much slower than you expected, and the output from the training run does not provide any obvious clues. Which of the following is most likely causing training to run slower than anticipated?

Q20.You are working on a project to build a continuous integration/continuous delivery (CI/CD) process using Kubeflow to automatically deploy a newly trained machine learning model to Google AI Platform Prediction. Two primary triggers in the process can result in the pipeline delivering a new model to production: (1) a developer updates model or pipeline code (2) new training data is available. You are responsible for testing the scenario when new training data triggers the process. Which of the following actions should you expect to occur when new training data is available?

Q21.You are in the process of developing a new binary classification machine learning model using a deep neural network and need a baseline to easily test the model's quality. Since this is a new model, there is not an existing model to compare to the new model. Which of the following should you choose to use as a baseline to access your models quality?

Q22.You are hired to help automate invoice processing for a company. You need to design a solution to process the invoices as quickly and accurately as possible, and the invoice data can also be verified by the workers manually if needed. The invoice data is uploaded to Google Cloud Storage every night. How should you design the solution in Google Cloud?

Q23.Your company is developing a product recommendation service for your eCommerce site. You have been provided the product catalog data and historical user event data. The company wants to use this service to increase the sales revenue. How do you load the data and design a recommendation system using Google Retail AI?

Q24.A company that provides computer vision and robotics to agricultural machinery is working on a new product that identifies and precisely treats plant species in the field. You are working on training a machine learning model for this project with roughly 100,000 labeled images of plants. You are using Google AI platform and are taking advantage of TPU accelerators to improve training times. You want to make sure reading in the large volume of images does not create a bottleneck during training. Which of the following solutions can help reduce bottleneck issues with data ingestion?

Q25.You are working on a machine learning model that uses PyTorch and are migrating the project from on-premise to the Google Cloud AI Platform. Your team is also using a few dependencies that are not related to machine learning. Your job is to recommend what steps the team needs to take to run this work on Cloud AI Platform Training. Which of the following solutions should you recommend for this machine learning project to run on Cloud AI Platform Training?

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