Smart Analytics, Machine Learning, and AI on GCP
All Quiz Answer
Introduction to Analytics and AI
Q1)What is the difference between AI and ML?
- AI is a discipline while ML is a toolset
Q2)What is the primary impact of ML?
- It allows business operations to scale
Prebuilt ML model APIs for Unstructured Data
Q1) Most business data is unstructured data, and mainly text
- True
Q2) Google Cloud's pretrained model APIs use:
- Google's models and Google's data
Big Data Analytics with Cloud AI Platform Notebooks
Q1) Which statements are true regarding AI Platform Notebooks?
- You can easily change hardware including adding and removing GPUs
- They use the latest open-source version of JupyterLab
- Notebook instances are standard GCE instances that live in your projects
Q2) AI Platform Notebooks contains a magic function to execute BigQuery
- True
Productionizing Custom ML Models
Q1)Which technology was developed to attack DevOps challenges in ML using Kubernetes and containers ?
- Kubeflow
Q2)AI Hub has templates for which of the following?
- All of the above
Custom Model building with SQL in BigQuery ML
Q1)You can train and evaluate machine learning models directly in BigQuery.
- True
Q2)BigQuery ML has support for which of the following modeling tasks:
- Regression
- Clustering
- Classification
Custom Model Building with Cloud AutoML
Q1) Cloud AutoML makes use of which of the following:
- Google's models and your data
Q2) Which of the following are valid techniqes for improving AutoML Vision and NLP models?
- Increase the amount of training data
- Ensure consistent labeling
- Increase the diversity and complexity of data
2 Comments
BigQuery ML has support for which of the following modeling tasks:
ReplyDeleteNice article... niyander
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