Free Professional-Machine-Learning-Engineer Exam Braindumps

You are responsible for building a unified analytics environment across a variety of on-premises data marts. Your company is experiencing data quality and security challenges when integrating data across the servers, caused by the use of a wide range of disconnected tools and temporary solutions. You need a fully managed, cloud-native data integration service that will lower the total cost of work and reduce repetitive work. Some members on your team prefer a codeless interface for building Extract, Transform, Load (ETL) process. Which service should you use?

1. A. Dataflow
2. B. Dataprep
3. C. Apache Flink
4. D. Cloud Data Fusion

Correct Answer: D

During batch training of a neural network, you notice that there is an oscillation in the loss. How should you adjust your model to ensure that it converges?

1. A. Increase the size of the training batch
2. B. Decrease the size of the training batch
3. C. Increase the learning rate hyperparameter
4. D. Decrease the learning rate hyperparameter

Correct Answer: C

You are building an ML model to detect anomalies in real-time sensor data. You will use Pub/Sub to handle incoming requests. You want to store the results for analytics and visualization. How should you configure the pipeline?

1. A. 1 = Dataflow, 2 - Al Platform, 3 = BigQuery
2. B. 1 = DataProc, 2 = AutoML, 3 = Cloud Bigtable
3. C. 1 = BigQuery, 2 = AutoML, 3 = Cloud Functions
4. D. 1 = BigQuery, 2 = Al Platform, 3 = Cloud Storage

Correct Answer: C

Your team is building an application for a global bank that will be used by millions of customers. You built a forecasting model that predicts customers1 account balances 3 days in the future. Your team will use the results in a new feature that will notify users when their account balance is likely to drop below $25. How should you serve your predictions?

1. A. 1. Create a Pub/Sub topic for each user* 2 Deploy a Cloud Function that sends a notification when your model predicts that a user's account balance will drop below the $25 threshold.
2. B. 1. Create a Pub/Sub topic for each user* 2. Deploy an application on the App Engine standard environment that sends a notification when your model predicts thata user's account balance will drop below the $25 threshold
3. C. 1. Build a notification system on Firebase* 2. Register each user with a user ID on the Firebase Cloud Messaging server, which sends a notification when the average of all account balance predictions drops below the $25 threshold
4. D. 1 Build a notification system on Firebase* 2. Register each user with a user ID on the Firebase Cloud Messaging server, which sends a notification when your model predicts that a user's account balance will drop below the $25 threshold

Correct Answer: B

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?

1. A. Create a tf.data.Dataset.prefetch transformation
2. B. Convert the images to tf .Tensor Objects, and then run Datase
3. C. from_tensor_slices{).
4. D. Convert the images to tf .Tensor Objects, and then run t
5. E. dat
6. F. Datase
7. G. from_tensors ().
8. H. Convert the images Into TFRecords, store the images in Cloud Storage, and then use the t
9. I. data API to read the images for training

Correct Answer: D