We may earn an affiliate commission when you visit our partners.
Course image
Course image
Coursera logo

Classify Text into Categories with the Natural Language API

Google Cloud Training

This is a self-paced lab that takes place in the Google Cloud console. In this lab you’ll learn how to classify text into categories using the Natural Language API.

Enroll now

What's inside

Syllabus

Classify Text into Categories with the Natural Language API
In this lab you’ll learn how to classify text into categories using the Natural Language API.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides cloud computing skills for software engineers, cloud engineers, and technical professionals
Course instructors are Google Cloud Training experts
Strong industry relevance for software engineers looking to enhance their toolkit
Requires proficiency in Natural Language Processing and basic Google Cloud knowledge

Save this course

Save Classify Text into Categories with the Natural Language API to your list so you can find it easily later:
Save

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Classify Text into Categories with the Natural Language API with these activities:
Refresh Your Python Skills
Refreshing your Python skills will help you to be more successful in this course.
Browse courses on Python
Show steps
  • Review the basics of Python syntax.
  • Complete a few Python coding exercises.
Find a Natural Language Processing Mentor
Having a mentor can provide you with guidance, support, and advice as you learn about natural language processing.
Show steps
  • Identify the qualities you want in a mentor.
  • Reach out to potential mentors and ask them if they are willing to mentor you.
  • Meet with your mentor regularly and discuss your progress.
Review 'Natural Language Processing with Python'
This book will provide a strong foundation in the fundamentals of natural language processing and will help you understand the concepts covered in the course.
Show steps
  • Read the first three chapters of the book.
  • Complete the exercises at the end of each chapter.
  • Create a simple natural language processing program using Python.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a Natural Language Processing Study Group
Joining a study group will allow you to connect with other learners, share knowledge, and get help with difficult concepts.
Show steps
  • Find a study group that meets your needs.
  • Attend study group meetings regularly.
  • Participate in discussions and help other learners.
Complete the Natural Language Processing Drills
These drills will provide you with practice in using the Natural Language Toolkit (NLTK) to perform common natural language processing tasks.
Show steps
  • Complete the exercises in the NLTK tutorial.
  • Create a program that uses NLTK to perform text classification.
  • Create a program that uses NLTK to perform named entity recognition.
Attend a Natural Language Processing Workshop
Attending a workshop will allow you to learn from experts in the field and get hands-on experience with natural language processing tools and techniques.
Show steps
  • Find a workshop that meets your needs.
  • Register for the workshop.
  • Attend the workshop and participate in the activities.
Create a Natural Language Processing Tutorial
Creating a tutorial will help you solidify your understanding of natural language processing and will also be a valuable resource for other learners.
Show steps
  • Choose a topic for your tutorial.
  • Write a step-by-step guide on how to perform the task.
  • Create code examples to illustrate your steps.
  • Publish your tutorial online.
Volunteer for a Natural Language Processing Project
Volunteering for a natural language processing project will allow you to gain practical experience and make a contribution to the community.
Show steps
  • Find a volunteer opportunity that meets your needs.
  • Apply for the volunteer position.
  • Participate in the volunteer project and complete your tasks.

Career center

Learners who complete Classify Text into Categories with the Natural Language API will develop knowledge and skills that may be useful to these careers:
Data Scientist
A Data Scientist uses data to solve business problems. This course may be useful to a Data Scientist as it provides an introduction to the concepts of data science, including text classification.
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning models for use in a variety of applications. This course may be useful to a Machine Learning Engineer as it provides an introduction to the concepts of machine learning, including text classification.
Business Analyst
A Business Analyst analyzes business processes and recommends solutions to improve efficiency. This course may be useful to a Business Analyst as it provides an introduction to the concepts of business analysis, including text classification.
Software Engineer
A Software Engineer designs, develops, and deploys software applications. This course may be useful to a Software Engineer as it provides an introduction to the concepts of software engineering, including text classification.
Marketing Analyst
A Marketing Analyst analyzes marketing data to understand customer behavior and make recommendations for improving marketing campaigns. This course may be useful to a Marketing Analyst as it provides an introduction to the concepts of marketing analytics, including text classification.
Product Manager
A Product Manager manages the development and launch of new products. This course may be useful to a Product Manager as it provides an introduction to the concepts of product management, including text classification.
Professor
A Professor teaches and conducts research at a college or university. This course may be useful to a Professor as it provides an introduction to the concepts of higher education, including text classification.
Technical Writer
A Technical Writer creates and edits technical documentation, such as user manuals, technical reports, and white papers. This course may be useful to a Technical Writer as it provides an introduction to the concepts of technical writing, including text classification.
Editor
An Editor reviews and edits written content for a variety of purposes, such as books, magazines, and websites. This course may be useful to an Editor as it provides an introduction to the concepts of editing, including text classification.
Museum curator
A Museum Curator manages and organizes museum collections and provides educational and research assistance to museum visitors. This course may be useful to a Museum Curator as it provides an introduction to the concepts of museum studies, including text classification.
Teacher
A Teacher teaches students at a variety of levels, from elementary school to college. This course may be useful to a Teacher as it provides an introduction to the concepts of teaching, including text classification.
Archivist
An Archivist preserves and manages historical documents and artifacts. This course may be useful to an Archivist as it provides an introduction to the concepts of archival science, including text classification.
Librarian
A Librarian manages and organizes library collections and provides reference and research assistance to library patrons. This course may be useful to a Librarian as it provides an introduction to the concepts of library science, including text classification.
Natural Language Processing Engineer
A Natural Language Processing Engineer designs, develops, tests, and deploys natural language processing (NLP) models for use in a variety of applications. This course may be useful to a Natural Language Processing Engineer as it provides an introduction to the concepts of natural language processing, including text classification.
Content Writer
A Content Writer creates and edits written content for a variety of purposes, such as websites, articles, and marketing materials. This course may be useful to a Content Writer as it provides an introduction to the concepts of content writing, including text classification.

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Classify Text into Categories with the Natural Language API.
Provides a comprehensive overview of natural language processing, covering topics such as text classification, sentiment analysis, and machine translation. It valuable resource for anyone who wants to learn more about the field of natural language processing.
Provides a comprehensive overview of deep learning algorithms for natural language processing. It covers topics such as text classification, sentiment analysis, and machine translation. It valuable resource for anyone who wants to learn how to use deep learning algorithms for natural language processing.
Provides a practical introduction to text analysis using Python. It covers topics such as text preprocessing, text classification, and text clustering. It valuable resource for anyone who wants to learn how to use text analysis for real-world applications.
Provides a comprehensive overview of the Natural Language Toolkit (NLTK), a popular Python library for natural language processing. It covers topics such as text preprocessing, text classification, and text clustering. It valuable resource for anyone who wants to learn how to use NLTK for natural language processing.
Provides a comprehensive overview of natural language processing using JavaScript. It covers topics such as text preprocessing, text classification, and text clustering. It valuable resource for anyone who wants to learn how to use JavaScript for natural language processing.
Provides a comprehensive overview of natural language processing using Go. It covers topics such as text preprocessing, text classification, and text clustering. It valuable resource for anyone who wants to learn how to use Go for natural language processing.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Classify Text into Categories with the Natural Language API.
Configuring and Deploying Windows SQL Server on Google...
Set Up and Configure a Cloud Environment in Google Cloud ...
Developing with Cloud Run
Set Up and Configure a Cloud Environment in Google Cloud ...
The Electronics Workbench: a Setup Guide
Datadog: Getting started with the Helm Chart
Exploring the Public Cryptocurrency Datasets Available in...
Build a Two Screen Flutter Application
Configure Palo Alto Firewalls in a Home Lab
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser