- (Exam Topic 5)
Which software libraries are supported by Cloud Machine Learning Engine?

1. A. Theano and TensorFlow
2. B. Theano and Torch
3. C. TensorFlow
4. D. TensorFlow and Torch

Correct Answer: C
Cloud ML Engine mainly does two things:
Enables you to train machine learning models at scale by running TensorFlow training applications in the cloud.
Hosts those trained models for you in the cloud so that you can use them to get predictions about new data.
Reference: https://cloud.google.com/ml-engine/docs/technical-overview#what_it_does

- (Exam Topic 6)
You want to automate execution of a multi-step data pipeline running on Google Cloud. The pipeline includes Cloud Dataproc and Cloud Dataflow jobs that have multiple dependencies on each other. You want to use managed services where possible, and the pipeline will run every day. Which tool should you use?

1. A. cron
2. B. Cloud Composer
3. C. Cloud Scheduler
4. D. Workflow Templates on Cloud Dataproc

Correct Answer: D

- (Exam Topic 5)
Which of the following are examples of hyperparameters? (Select 2 answers.)

1. A. Number of hidden layers
2. B. Number of nodes in each hidden layer
3. C. Biases
4. D. Weights

Correct Answer: AB
If model parameters are variables that get adjusted by training with existing data, your hyperparameters are the variables about the training process itself. For example, part of setting up a deep neural network is deciding how many "hidden" layers of nodes to use between the input layer and the output layer, as well as how many nodes each layer should use. These variables are not directly related to the training data at all. They are configuration variables. Another difference is that parameters change during a training job, while the hyperparameters are usually constant during a job.
Weights and biases are variables that get adjusted during the training process, so they are not hyperparameters. Reference: https://cloud.google.com/ml-engine/docs/hyperparameter-tuning-overview

- (Exam Topic 1)
Your company’s customer and order databases are often under heavy load. This makes performing analytics against them difficult without harming operations. The databases are in a MySQL cluster, with nightly backups taken using mysqldump. You want to perform analytics with minimal impact on operations. What should you do?

1. A. Add a node to the MySQL cluster and build an OLAP cube there.
2. B. Use an ETL tool to load the data from MySQL into Google BigQuery.
3. C. Connect an on-premises Apache Hadoop cluster to MySQL and perform ETL.
4. D. Mount the backups to Google Cloud SQL, and then process the data using Google Cloud Dataproc.

Correct Answer: C

- (Exam Topic 6)
Your United States-based company has created an application for assessing and responding to user actions. The primary table’s data volume grows by 250,000 records per second. Many third parties use your application’s APIs to build the functionality into their own frontend applications. Your application’s APIs should comply with the following requirements:
Single global endpoint
ANSI SQL support
Consistent access to the most up-to-date data What should you do?

1. A. Implement BigQuery with no region selected for storage or processing.
2. B. Implement Cloud Spanner with the leader in North America and read-only replicas in Asia and Europe.
3. C. Implement Cloud SQL for PostgreSQL with the master in Norht America and read replicas in Asia and Europe.
4. D. Implement Cloud Bigtable with the primary cluster in North America and secondary clusters in Asia and Europe.

Correct Answer: B