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Bhaskarjit Sarmah
In this 2-hour long project-based course, you will understand the business problem and the dataset and learn how to generate a hypothesis to create new features based on existing data. You will learn to perform text pre-processing and creating custom transformers to generate new features in to pass into the machine learning pipeline. And you will implement NLP pipeline creating your own custom transformers and build a text classification model.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/d094kv/build
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Investigates text pre-processing, which is standard in NLP
Enhances students' NLP skills, which are crucial for data scientists
Emphasizes the creation of custom transformers in NLP, a highly relevant skillset
Includes hands-on labs and interactive materials, providing practical experience
Assumes knowledge of NLP techniques, catering to intermediate learners
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Reviews summary
Nlp pipeline development with scikit-learn
This project-based course is not without its drawbacks. However, the positive sentiment suggests that most learners who leave reviews are happy with the course and find it to be a good use of time.
The course includes a nice mini project.
"Nice mini project"
The course provides clear instructions.
"Clear instructions"
The instructor is inactive during discussions.
"instructor is inactive on discussion"
The course content is basic.
"This is easier than any intro to NLP. If you want to learn something, just google and go to a kaggle project page."
The course materials are lacking and not updated.
"Materials not provided and not updated as well"
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 Build NLP pipelines using scikit-learn with these
activities:
Review Python programming fundamentals
Show steps
Strengthen your foundation in Python programming before starting the course.
Browse courses on
Python
Show steps
-
Review online tutorials or documentation on Python syntax and basic data structures.
-
Complete practice problems or exercises to test your understanding.
Read 'Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit'
Show steps
Review the fundamentals of natural language processing (NLP) and text analysis by reading a book that covers these topics.
View
Natural Language Processing with Python:...
on Amazon
Show steps
-
Purchase and read the book.
-
Take notes on key concepts and techniques.
-
Complete the exercises and assignments in the book.
Follow tutorials on NLP topics
Show steps
Expand your knowledge and skills in specific NLP areas by following guided tutorials.
Browse courses on
Natural Language Processing
Show steps
-
Identify areas where you need additional knowledge or skills.
-
Search for and find relevant tutorials.
-
Follow the tutorials and complete the exercises.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a study group or discussion forum
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Connect with other learners and collaborate on NLP-related topics.
Browse courses on
Natural Language Processing
Show steps
-
Find a study group or discussion forum that aligns with your interests.
-
Participate in discussions and ask questions.
-
Share your knowledge and insights with others.
Complete NLP exercises on Kaggle
Show steps
Reinforce your understanding of NLP concepts by practicing on real-world datasets.
Browse courses on
Natural Language Processing
Show steps
-
Create an account on Kaggle.
-
Find and join NLP competitions or datasets.
-
Submit your solutions and compare them with others.
Write a blog post or article on NLP
Show steps
Share your knowledge and understanding of NLP by writing a blog post or article.
Browse courses on
Natural Language Processing
Show steps
-
Choose a topic related to NLP.
-
Research and gather information.
-
Write and edit the blog post or article.
-
Publish and promote your content.
Record a video tutorial on NLP
Show steps
Contribute to the community and share your knowledge by creating a video tutorial on NLP.
Browse courses on
Natural Language Processing
Show steps
-
Choose a topic that you are knowledgeable about.
-
Create an outline and storyboard for your video.
-
Record and edit your video.
-
Publish and promote your video tutorial.
Review Python programming fundamentals
Show steps
Strengthen your foundation in Python programming before starting the course.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review online tutorials or documentation on Python syntax and basic data structures.
- Complete practice problems or exercises to test your understanding.
Read 'Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit'
Show steps
Review the fundamentals of natural language processing (NLP) and text analysis by reading a book that covers these topics.
View
Natural Language Processing with Python:...
on Amazon
Show steps
Show steps
Show steps
- Purchase and read the book.
- Take notes on key concepts and techniques.
- Complete the exercises and assignments in the book.
Follow tutorials on NLP topics
Show steps
Expand your knowledge and skills in specific NLP areas by following guided tutorials.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Identify areas where you need additional knowledge or skills.
- Search for and find relevant tutorials.
- Follow the tutorials and complete the exercises.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a study group or discussion forum
Show steps
Connect with other learners and collaborate on NLP-related topics.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Find a study group or discussion forum that aligns with your interests.
- Participate in discussions and ask questions.
- Share your knowledge and insights with others.
Complete NLP exercises on Kaggle
Show steps
Reinforce your understanding of NLP concepts by practicing on real-world datasets.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Create an account on Kaggle.
- Find and join NLP competitions or datasets.
- Submit your solutions and compare them with others.
Write a blog post or article on NLP
Show steps
Share your knowledge and understanding of NLP by writing a blog post or article.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Choose a topic related to NLP.
- Research and gather information.
- Write and edit the blog post or article.
- Publish and promote your content.
Record a video tutorial on NLP
Show steps
Contribute to the community and share your knowledge by creating a video tutorial on NLP.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Choose a topic that you are knowledgeable about.
- Create an outline and storyboard for your video.
- Record and edit your video.
- Publish and promote your video tutorial.
Career center
Learners who complete Build NLP pipelines using scikit-learn will develop knowledge and skills
that may be useful to these careers:
Marketing Manager
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. NLP is increasingly being used to target marketing campaigns and measure their effectiveness. This course may be helpful for Marketing Managers by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
Project Manager
Project Manager
Project Managers are responsible for planning and executing projects. NLP is increasingly being used to improve project management processes and track project progress. This course may be helpful for Project Managers by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
Sales Manager
Sales Manager
Sales Managers are responsible for leading sales teams and generating revenue. NLP is increasingly being used to automate sales processes and improve customer relationships. This course may be helpful for Sales Managers by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems. NLP pipelines are often used to extract insights from text data, which can then be used to make decisions. This course may be helpful for Data Scientists by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build, deploy, and maintain machine learning models. Machine learning models are algorithms that can learn from data and make predictions. NLP pipelines are often used as a preprocessing step for machine learning models. This course may be helpful by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
Business Analyst
Business Analyst
Business Analysts use data to identify and solve business problems. NLP is increasingly being used by Business Analysts to extract insights from text data, which can then be used to make decisions. This course may be helpful for Business Analysts by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. NLP is increasingly being used in software applications to improve user experience and automate tasks. This course may be helpful for Software Engineers by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. NLP is increasingly being used to improve the user experience of products. This course may be helpful for Product Managers by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
Operations Manager
Operations Manager
Operations Managers are responsible for the day-to-day operations of a business. NLP is increasingly being used to automate operations processes and improve efficiency. This course may be helpful for Operations Managers by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
Portfolio Manager
Portfolio Manager
Portfolio Managers are responsible for managing a portfolio of investments. NLP is increasingly being used to analyze investment data and identify investment opportunities. This course may be helpful for Portfolio Managers by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
Risk Manager
Risk Manager
Risk Managers are responsible for identifying and mitigating risks. NLP is increasingly being used to analyze risk data and identify potential risks. This course may be helpful for Risk Managers by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
Customer Success Manager
Customer Success Manager
Customer Success Managers are responsible for ensuring that customers are successful with a product or service. NLP is increasingly being used to improve customer support and identify customer needs. This course may be helpful for Customer Success Managers by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
Program Manager
Program Manager
Program Managers are responsible for managing a portfolio of projects. NLP is increasingly being used to improve program management processes and track program progress. This course may be helpful for Program Managers by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
Natural Language Processing Engineer
Natural Language Processing Engineer
A Natural Language Processing Engineer builds and maintains NLP pipelines within machine learning models. An NLP pipeline is a sequence of text processing steps used to transform raw text into a format that can be analyzed by a machine learning algorithm. Natural Language Processing Engineers typically hold a Master's or PhD in Computer Science. This course may be helpful by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
Compliance Manager
Compliance Manager
Compliance Managers are responsible for ensuring that a company complies with laws and regulations. NLP is increasingly being used to analyze compliance data and identify potential compliance risks. This course may be helpful for Compliance Managers by providing a foundation in the principles of NLP and the tools used to build NLP pipelines.
For more career information including salaries, visit:
OpenCourser.com/course/d094kv/build
Reading list
We've selected seven 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
Build NLP pipelines using scikit-learn.
Provides a comprehensive overview of deep learning using Python, and valuable resource for anyone looking to learn more about the field.
Save
Provides a comprehensive overview of NLP using transformers, and valuable resource for anyone looking to learn more about the field.
Provides a practical guide to NLP using Python, and great resource for anyone looking to learn more about the field.
Provides a comprehensive overview of Hadoop, a popular big data processing framework.
Provides a comprehensive overview of the Natural Language Toolkit (NLTK), a popular Python library for NLP.
Provides a comprehensive overview of speech and language processing, and valuable resource for anyone looking to learn more about the field.
Provides a comprehensive overview of statistical learning, and valuable resource for anyone looking to learn more about the field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/d094kv/build
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Bhaskarjit Sarmah
Good to know
Investigates text pre-processing, which is standard in NLP
Enhances students' NLP skills, which are crucial for data scientists
Emphasizes the creation of custom transformers in NLP, a highly relevant skillset
Includes hands-on labs and interactive materials, providing practical experience
Assumes knowledge of NLP techniques, catering to intermediate learners
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