Smart Analytics, Machine Learning, and AI on GCP Coursera Quiz Answers

All Weeks Smart Analytics, Machine Learning, and AI on GCP Coursera Quiz Answers

Incorporating machine learning into data pipelines increases the ability of businesses to extract insights from their data. This course covers several ways machine learning can be included in data pipelines on Google Cloud depending on the level of customization required.

For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to produce machine learning solutions using Kubeflow. Learners will get hands-on experience building machine learning models on Google Cloud using QwikLabs.

This is the fourth course of the Data Engineering on Google Cloud series.

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Introduction to Analytics and AI Quiz Answers

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 Quiz Answers

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 Quiz Answers

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 Quiz Answers

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 Quiz Answers

Q1. Cloud AutoML makes use of which of the following:

  • Google’s models and your data

Q2. Which of the following are valid techniques for improving AutoML Vision and NLP models?

  • Increase the amount of training data
  • Ensure consistent labeling
  • Increase the diversity and complexity of data
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This course is intended for audiences of all experiences who are interested in learning about new skills in a business context; there are no prerequisite courses.

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