Black Friday Special 70% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: Board70

Machine Learning Engineer Professional-Machine-Learning-Engineer Passing Score

Page: 5 / 21
Question 20

You work with a learn of researchers lo develop state-of-the-art algorithms for financial analysis. Your team develops and debugs complex models in TensorFlow. You want to maintain the ease of debugging while also reducing the model training time. How should you set up your training environment?

Options:

A.

Configure a v3-8 TPU VM.

B.

Configure a v3-8 TPU node.

C.

Configure a c2-standard-60 VM without GPUs.

D, Configure a n1-standard-4 VM with 1 NVIDIA P100 GPU.

Question 21

You work with a data engineering team that has developed a pipeline to clean your dataset and save it in a Cloud Storage bucket. You have created an ML model and want to use the data to refresh your model as soon as new data is available. As part of your CI/CD workflow, you want to automatically run a Kubeflow Pipelines training job on Google Kubernetes Engine (GKE). How should you architect this workflow?

Options:

A.

Configure your pipeline with Dataflow, which saves the files in Cloud Storage After the file is saved, start the training job on a GKE cluster

B.

Use App Engine to create a lightweight python client that continuously polls Cloud Storage for new files As soon as a file arrives, initiate the training job

C.

Configure a Cloud Storage trigger to send a message to a Pub/Sub topic when a new file is available in a storage bucket. Use a Pub/Sub-triggered Cloud Function to start the training job on a GKE cluster

D.

Use Cloud Scheduler to schedule jobs at a regular interval. For the first step of the job. check the timestamp of objects in your Cloud Storage bucket If there are no new files since the last run, abort the job.

Question 22

You were asked to investigate failures of a production line component based on sensor readings. After receiving the dataset, you discover that less than 1% of the readings are positive examples representing failure incidents. You have tried to train several classification models, but none of them converge. How should you resolve the class imbalance problem?

Options:

A.

Use the class distribution to generate 10% positive examples

B.

Use a convolutional neural network with max pooling and softmax activation

C.

Downsample the data with upweighting to create a sample with 10% positive examples

D.

Remove negative examples until the numbers of positive and negative examples are equal

Question 23

You work on an operations team at an international company that manages a large fleet of on-premises servers located in few data centers around the world. Your team collects monitoring data from the servers, including CPU/memory consumption. When an incident occurs on a server, your team is responsible for fixing it. Incident data has not been properly labeled yet. Your management team wants you to build a predictive maintenance solution that uses monitoring data from the VMs to detect potential failures and then alerts the service desk team. What should you do first?

Options:

A.

Train a time-series model to predict the machines’ performance values. Configure an alert if a machine’s actual performance values significantly differ from the predicted performance values.

B.

Implement a simple heuristic (e.g., based on z-score) to label the machines’ historical performance data. Train a model to predict anomalies based on this labeled dataset.

C.

Develop a simple heuristic (e.g., based on z-score) to label the machines’ historical performance data. Test this heuristic in a production environment.

D.

Hire a team of qualified analysts to review and label the machines’ historical performance data. Train a model based on this manually labeled dataset.

Page: 5 / 21
Exam Name: Google Professional Machine Learning Engineer
Last Update: Nov 22, 2024
Questions: 285
Professional-Machine-Learning-Engineer pdf

Professional-Machine-Learning-Engineer PDF

$25.5  $84.99
Professional-Machine-Learning-Engineer Engine

Professional-Machine-Learning-Engineer Testing Engine

$28.5  $94.99
Professional-Machine-Learning-Engineer PDF + Engine

Professional-Machine-Learning-Engineer PDF + Testing Engine

$40.5  $134.99