Smart Analytics, Machine Learning, and AI on Google Cloud Coursera Quiz Answers
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Smart Analytics, Machine Learning, and AI on Google Cloud Coursera Quiz Answers
There are 8 modules in this course
Introduction to Analytics and AI Quiz Answers
Question 1)
What is the difference between AI and ML?
- AI is a discipline while ML is a toolset
Question 2)
What is the primary impact of ML?
- It allows business operations to scale
Prebuilt ML model APIs for Unstructured Data Quiz Answers
Question 1)
Most business data is unstructured data, and mainly text
- True
Question 2)
Google Cloud’s pretrained model APIs use:
- Google’s models and Google’s data
Big Data Analytics with Cloud AI Platform Notebooks Quiz Answers
Question 1)
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
Question 2)
AI Platform Notebooks contains a magic function to execute BigQuery
- True
Productionizing Custom ML Models Quiz Answers
Question 1)
Which technology was developed to attack DevOps challenges in ML using Kubernetes and containers ?
- Kubeflow
Question 2)
AI Hub has templates for which of the following?
- All of the above
Custom Model building with SQL in BigQuery ML Quiz Answers
Question 1)
You can train and evaluate machine learning models directly in BigQuery.
- True
Question 2)
BigQuery ML has support for which of the following modeling tasks:
- Regression
- Clustering
- Classification
Custom Model Building with Cloud AutoML Quiz Answers
Question 1)
Cloud AutoML makes use of which of the following:
- Google’s models and your data
Question 2)
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