1. A team of researchers is analyzing buying patterns of customers of a national grocery store chain. They are especially interested in sets of products that customers frequently by together. The researchers plan to use association rules for this frequent pattern mining. What machine learning option in GCP would you recommend?

2. A startup company is building an anomaly detection service for manufacturing equipment. IoT sensors on manufacturing equipment transmit data on machine performance every 30 seconds. The service will initially support up to 5,000 sensors, but it will eventually grow to millions of sensors. The data will be stored in Cloud Bigtable after it is preprocessed and transformed by a Cloud Dataflow workflow. What service should be used to ingest the IoT data?

3. A developer has built a machine learning model to predict the category of new stories. The possible values are politics, economics, business, health, science, and local news. The developer has tried several algorithms, but the model accuracy is poor even when evaluating the model on using the training data. This is an example of what kind of potential problem with a machine learning model?

4. A developer with limited knowledge of machine learning is attempting to build a machine learning model. The developer is using data collected from a data lake with minimal data preparation. After models are built, they are evaluated. Model performance is poor. The developer has asked for your help to reduce the time needed to train the model and increase the quality of model predictions. What would you do first with the developer?

5. A machine learning engineer has just started a new project. The engineer will be building a recommendation engine for an e-commerce site. Data from several services will be used, including data about products, customers, and inventory. The data is currently available in a data lake and stored in its raw, unprocessed form. What is the first thing you would recommend the machine learning engineer do to start work on the project?

6. Your e-commerce company deployed a product recommendation system six months ago. The system uses a machine learning model trained using historical sales data from the previous year. The model performed well initially. When customers were shown product recommendations, the average sale value increased by 14 percent. In the past month, the model has generated an average increase of only 2 percent. The model has not changed since it was deployed six months ago. What could be the cause of the decrease in effectiveness, and what would you recommend to correct it?

7. The chief financial officer of your company would like to build a program to predict which customers will likely be late paying their bills. The company has an enterprise data warehouse in BigQuery containing all the data related to customers, billing, and payments. The company does not have anyone with machine learning experience, but it does have analysts and data scientists experienced in SQL, Python, and Java. The analysts and data scientists will generate and test a large number of models, so they prefer fast model building. What service would you recommend using to build the model?

8. A machine learning engineer is in the process of building a model for classifying fraudulent transactions. They are using a neural network and need to decide how many nodes and layers to use in the model. They are experimenting with several different combinations of number of nodes and number of layers. What data should they use to evaluate the quality of models being developed with each combination of settings?

9. An analyst would like to build a machine learning model to classify rows of data in a dataset. There are two categories into which the rows can be grouped: Type A and TypeB. The dataset has over 1 million rows, and each row has 32 attributes or features. The analyst does not know which features are important. A labeled training set is available with a sufficient number of rows to train a model. The analyst would like the most accurate model possible with the least amount of effort on the analyst’s part. What would you recommend?

10. A developer has built a machine learning model to predict the category of new stories. The possible values are politics, economics, business, health, science, and local news. The developer has tried several algorithms, but the model accuracy is quite high when evaluating the model using the training data but quite low when evaluating using test data. What would you recommend to correct this problem?

11. You have been tasked with helping to establish ML pipelines for your department. The models will be trained using data from several sources, including several enterprise transaction processing systems and third-party data provider datasets. Data will arrive in batches. Although you know the structure of the data now, you expect that it will change, and you will not know about the changes until the data arrives. You want to ensure that your ingestion process can store the data in whatever structure it arrives in. After the data is ingested, you will transform it as needed. What storage system would you use for batch ingestion?

12. A startup company is developing software to analyze images of traffic in order to understand congestion patterns better and how to avoid them. The software will analyze images that are taken every minute from hundreds of locations in a city. The software will need to identify cars, trucks, cyclists, pedestrians, and buildings. The data on object identities will be used by analysis algorithms to detect daily patterns, which will then be used by traffic engineers to devise new traffic flow patterns. What GCP service would you use for this?