Analyze and Retrieve Information from Text Using Google Cloud Natural Language
Google Cloud Natural Language is a machine learning service that enables you to analyze and retrieve different kinds of information from text, or from a text document, uploaded to Cloud Storage. By using Google's pre-created machine learning models, you can extract information such as sentiments, entities, content classifications, and syntax. This way, you can carry out text analysis and retrieve all the entities in a piece of text, with related information, or understand the sentiment expressed by a piece of text. By using Google Cloud Natural Language, you will use the same machine learning models that Google uses for its search engine. This ensures the speed and reliability of the retrieved information. If you want more information on Cloud Natural Language, follow this link.
In this lab, you will use Cloud Natural Language to perform entity analysis and sentiment analysis.
Upon completion of this lab you will be able to:
- Perform text analysis to retrieve entities described in a document
- Understand sentiments by analyzing a text document
This lab is intended for:
- Google Cloud Professional Data Engineer (PDE) candidates
- Data Engineers who want to build machine learning solutions using Google's pre-defined models
- Individuals who want to implement text analysis solutions
This lab has no prerequisites.
December 4th, 2023 - Updated instructions to clarify results
February 15th, 2023 - Updated the instructions and screenshots to reflect the latest UI
December 20th, 2021 - Removed references to Cloud Shell (Lab commands should be entered into the ca-lab-vm browser terminal)
Stefano studies Computer Science and is passionate about technology. He loves working with Cloud services and learning all the best practices for them. Google Cloud Platform and Amazon Web Services are the cloud providers he prefers. He is a Google Cloud Certified Associate Cloud Engineer. Node.js is the programming language he always uses to code. When he's not involved in studying or working, Stefano loves riding his motorbike and exploring new places.