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NEW QUESTION 42
Your team is working on building a machine learning model. There are a bunch of terminologies that are being used. What is an "instance" or an "example"?

• A. An input variable is used in making predictions. E.g. number of rooms in a house price prediction model.
• B. The "knobs" that you tweak during successive runs of training a model. E.g. learning rate
• C. One row of a dataset containing one or more input columns and possibly a prediction result.
• D. An answer for a prediction task, either the answer produced by a machine learning system or the right answer supplied in training data. E.g. image contains a "cat".

Answer: C

Explanation:
One row of a dataset containing one or more input columns and possibly a prediction result.

https://developers.google.com/machine-learning/guides/rules-of-ml#terminology

NEW QUESTION 43
What type of cloud computing service provides raw compute, storage, and network, organized in ways that are familiar to physical data centers?

• A. Platform as a Service.
• B. Infrastructure as a Service.
• C. Software as a Service.
• D. Database as a Service.

Answer: B

Explanation:
What is Infrastructure as a service :
IaaS (infrastructure as a service) is a computing model that offers resources on-demand to businesses and individuals via the cloud.
IaaS is attractive because acquiring computing resources to run applications or store data the traditional way requires time and capital. Enterprises must purchase equipment through procurement processes that can take months. They must invest in physical spaces: typically specialized rooms with power and cooling. And after deploying the systems, enterprises need IT, professionals, to manage them.
All this is challenging to scale when demand spikes or the business grows. Enterprises risk running out of capacity or overbuilding and ending up with infrastructure that suffers from low utilization.
These challenges are why IaaS use is steadily growing. Learn more about Compute Engine, Cloud Storage, etc.

NEW QUESTION 44
Your company provides car maintenance services. It is conducting an internal hackathon to identify new ideas that could expand their business. The teams have pitched different ideas and have started working on it. They have to present their application to the judges within 48 hours. A presentation alone is not enough; they have to demonstrate a working proof of concept. The team that you are mentoring is going to recommend additional ser-vices to drive in customers based on the brand of car they drive in. They need to be able to identify what brand of car the customer has, based on a photograph automatically taken at entry. They have already discovered an open source database of car images collected by online enthusiasts. How should they implement this solution?

• A. Use TensorFlow to create a model that will identify the car brands; use the available data to train the model.
• B. Use AutoML Image - upload the images and let it create a working model for you.
• C. Use Cloud Vision AI that is able to detect logos. Write only the code to integrate in-to your workflow.
• D. Use Deep Learning Containers that are preconfigured and optimized containers for deep learning environments.

Answer: B

Explanation:
It would be most straightforward to use AutoML Image. Put the images in Cloud Storage, point to it from AutoML, and start the model building process.
Reference Link- https://cloud.google.com/automl

NEW QUESTION 45
Which Google Cloud product gives you a consistent platform for multi-cloud application deployments and extends other Google Cloud services to your environment?

• A. Google Kubernetes Engine
• B. Virtual Public Cloud
• C. Compute Engine
• D. Anthos

Answer: D

NEW QUESTION 46
......

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