Q. What is a common use case for cloud ML services in business?
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A.
Data storage
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B.
Predictive maintenance
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C.
Basic data entry
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D.
Manual reporting
Solution
Predictive maintenance is a common use case, where cloud ML services analyze data to predict equipment failures.
Correct Answer:
B
— Predictive maintenance
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Q. What is a common use case for cloud ML services in businesses?
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A.
Data storage only
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B.
Real-time fraud detection
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C.
Manual data entry
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D.
Basic spreadsheet calculations
Solution
Real-time fraud detection is a common use case for cloud ML services, leveraging machine learning to identify fraudulent activities.
Correct Answer:
B
— Real-time fraud detection
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Q. What is a key feature of neural networks in cloud ML services?
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A.
They require no data preprocessing
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B.
They can model complex patterns
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C.
They are only used for image processing
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D.
They are less efficient than traditional algorithms
Solution
Neural networks are capable of modeling complex patterns in data, making them suitable for various applications in cloud ML.
Correct Answer:
B
— They can model complex patterns
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Q. What is a key feature of neural networks offered by cloud ML services?
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A.
Manual feature extraction
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B.
Automatic feature learning
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C.
Limited scalability
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D.
Static architecture
Solution
Neural networks in cloud ML services can automatically learn features from data, reducing the need for manual feature extraction.
Correct Answer:
B
— Automatic feature learning
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Q. What is a key feature of neural networks used in cloud ML services?
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A.
Linear regression
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B.
Feature engineering
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C.
Layered architecture
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D.
Decision trees
Solution
Neural networks are characterized by their layered architecture, which allows them to learn complex patterns in data.
Correct Answer:
C
— Layered architecture
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Q. What is a potential drawback of using cloud ML services?
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A.
High initial investment
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B.
Data privacy concerns
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C.
Limited computational power
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D.
Inflexible pricing models
Solution
Data privacy concerns can arise when using cloud ML services, as sensitive data may be processed off-site.
Correct Answer:
B
— Data privacy concerns
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Q. What is a primary benefit of using cloud ML services?
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A.
Increased hardware costs
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B.
Scalability and flexibility
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C.
Limited accessibility
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D.
Complex setup process
Solution
Cloud ML services provide scalability and flexibility, allowing users to easily adjust resources based on demand.
Correct Answer:
B
— Scalability and flexibility
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Q. What is the primary purpose of using cloud ML services for data scientists?
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A.
To avoid coding
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B.
To access large datasets and compute power
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C.
To eliminate the need for data cleaning
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D.
To reduce collaboration
Solution
Cloud ML services provide data scientists with access to large datasets and significant compute power, enhancing their analytical capabilities.
Correct Answer:
B
— To access large datasets and compute power
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Q. What is the role of AutoML in cloud ML services?
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A.
To automate data entry tasks
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B.
To simplify the model training process
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C.
To replace human data scientists entirely
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D.
To provide manual coding tools
Solution
AutoML simplifies the model training process by automating tasks such as feature selection and hyperparameter tuning.
Correct Answer:
B
— To simplify the model training process
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Q. What type of learning is primarily supported by cloud ML services for predictive analytics?
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A.
Unsupervised learning
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B.
Reinforcement learning
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C.
Supervised learning
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D.
Semi-supervised learning
Solution
Cloud ML services typically support supervised learning for predictive analytics, where models are trained on labeled data.
Correct Answer:
C
— Supervised learning
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Q. What type of learning is typically used in cloud ML services for predictive analytics?
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A.
Unsupervised learning
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B.
Reinforcement learning
-
C.
Supervised learning
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D.
Semi-supervised learning
Solution
Supervised learning is commonly used in cloud ML services for tasks like predictive analytics, where labeled data is available.
Correct Answer:
C
— Supervised learning
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Q. Which cloud ML service feature allows for easy deployment of models?
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A.
Model versioning
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B.
Data cleaning
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C.
Manual coding
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D.
Local execution
Solution
Model versioning is a feature that facilitates easy deployment and management of different model versions in cloud ML services.
Correct Answer:
A
— Model versioning
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Q. Which cloud ML service is known for its AutoML capabilities?
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A.
Amazon SageMaker
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B.
Microsoft Azure ML
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C.
IBM Watson
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D.
All of the above
Solution
All of the mentioned services, including Amazon SageMaker, Microsoft Azure ML, and IBM Watson, offer AutoML capabilities.
Correct Answer:
D
— All of the above
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Q. Which cloud ML service is specifically designed for building and deploying machine learning models?
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A.
Google BigQuery
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B.
AWS SageMaker
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C.
Microsoft Excel
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D.
Dropbox
Solution
AWS SageMaker is a cloud ML service designed for building, training, and deploying machine learning models at scale.
Correct Answer:
B
— AWS SageMaker
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Q. Which evaluation metric is commonly used to assess the performance of classification models in cloud ML services?
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A.
Mean Squared Error
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B.
Accuracy
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C.
Silhouette Score
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D.
R-squared
Solution
Accuracy is a common evaluation metric for classification models, measuring the proportion of correct predictions.
Correct Answer:
B
— Accuracy
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Q. Which of the following best describes 'AutoML' in cloud ML services?
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A.
Automated machine learning processes
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B.
Manual model tuning
-
C.
Basic data visualization
-
D.
Static model training
Solution
AutoML refers to automated machine learning processes that simplify the model development lifecycle.
Correct Answer:
A
— Automated machine learning processes
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Q. Which of the following is a common cloud ML service provider?
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A.
Google Cloud AI
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B.
Localhost ML
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C.
Desktop ML Suite
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D.
Offline AI Tools
Solution
Google Cloud AI is a well-known provider of cloud-based machine learning services.
Correct Answer:
A
— Google Cloud AI
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Q. Which of the following is an example of unsupervised learning in cloud ML services?
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A.
Image classification
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B.
Customer segmentation
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C.
Spam detection
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D.
Sentiment analysis
Solution
Customer segmentation is an example of unsupervised learning, where the model identifies patterns in data without labeled outcomes.
Correct Answer:
B
— Customer segmentation
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Q. Which of the following is NOT a characteristic of cloud ML services?
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A.
On-demand resource allocation
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B.
High upfront costs
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C.
Collaboration features
-
D.
Access to large datasets
Solution
High upfront costs are not a characteristic of cloud ML services, which typically operate on a pay-as-you-go model.
Correct Answer:
B
— High upfront costs
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