Your company built a TensorFlow neutral-network model with a large number of neurons and layers. The model fits well for the training data. However, when tested against new data, it performs poorly. What method can you employ to address this?

• A.Threading
• B.Serialization
• C.Dropout Methods
• D.Dimensionality Reduction

Comment: *

Name: *

Email: *

Verification: *

A shipping company has live package-tracking data that is sent to an Apache Kafka stream in real time. This is then loaded into BigQuery. Analysts in your company want to query the tracking data in BigQuery to analyze geospatial trends in the lifecycle of a package. The table was originally created with ingest-date partitioning.
Over time, the query processing time has increased. You need to implement a change that would improve query performance in BigQuery. What should you do?

• A.Tier older data onto Google Cloud Storage files and create a BigQuery table using GCS as an external data source.
• B.Implement clustering in BigQuery on the ingest date column.
• C.Implement clustering in BigQuery on the package-tracking ID column.
• D.Re-create the table using data partitioning on the package delivery date.

Comment: *

Name: *

Email: *

Verification: *

Which of these statements about BigQuery caching is true?

• A.By default, a query's results are not cached.
• B.BigQuery caches query results for 48 hours.
• C.Query results are cached even if you specify a destination table.
• D.There is no charge for a query that retrieves its results from cache.

Comment: *

Name: *

Email: *

Verification: *

Which of the following is NOT one of the three main types of triggers that Dataflow supports?

• A.Trigger based on element size in bytes
• B.Trigger that is a combination of other triggers
• C.Trigger based on element count
• D.Trigger based on time

Comment: *

Name: *

Email: *

Verification: *

Your company has hired a new data scientist who wants to perform complicated analyses across very large datasets stored in Google Cloud Storage and in a Cassandra cluster on Google Compute Engine.
The scientist primarily wants to create labelled data sets for machine learning projects, along with some visualization tasks. She reports that her laptop is not powerful enough to perform her tasks and it is slowing her down. You want to help her perform her tasks. What should you do?

• A.Run a local version of Jupiter on the laptop.
• B.Grant the user access to Google Cloud Shell.
• C.Host a visualization tool on a VM on Google Compute Engine.
• D.Deploy Google Cloud Datalab to a virtual machine (VM) on Google Compute Engine.

Comment: *

Name: *

Email: *

Verification: *