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Building Features from Text Data in Microsoft Azure

Michael Heydt
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Natural Language Processing Microsoft Azure Machine Learning Service Document Tokenization Stopword Removal Frequency Filtering Stemming Lemmatization

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Read about what's good
what should give you pause
and possible dealbreakers
Provides hands-on experience with Microsoft Azure Machine Learning Service virtual machines, ensuring familiarity with industry-standard tools
Taught by Michael Heydt, recognized for expertise in text data analysis and machine learning
Focuses on creating text features for machine learning models, aligning with the industry need for accurate data representation
Covers techniques such as text tokenization, frequency filtering, and n-gram identification, providing a comprehensive understanding of natural language processing
May require prior knowledge in machine learning, as it assumes familiarity with concepts like models and feature vectors

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Activities

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Career center

Learners who complete Building Features from Text Data in Microsoft Azure will develop knowledge and skills that may be useful to these careers:
Natural Language Processing Engineer
Natural Language Processing Engineers specialize in developing and using natural language processing techniques to solve real-world problems. This course teaches Natural Language Processing Engineers how to use Microsoft Azure to perform natural language processing tasks such as document tokenization, stopword removal, and n-gram identification. They will also learn how to represent text data in the form of vectors using one-hot encoding, frequency based encoding, and hashing. This knowledge will help Natural Language Processing Engineers build more effective natural language processing applications.
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Data Scientist
Data Scientists take text data and use it to train machine learning models. This course shows Data Scientists how to transform text data into features that machine learning models can consume. Using Microsoft Azure, Data Scientists will learn how to perform natural language processing tasks such as document tokenization and part-of-speech tagging, and how to represent text data in the form of vectors using one-hot encoding, frequency based encoding, and hashing. This course may also be useful for Data Scientists who want to gain an understanding of how to generate word embeddings using the BERT model.
See salaries and explore the career path for Data Scientist
Machine Learning Engineer
Machine Learning Engineers work with Data Scientists to develop and deploy machine learning models. This course teaches Machine Learning Engineers how to prepare text data for use in machine learning models. They will learn how to use document tokenization to break text down into meaningful units, stemming and lemmatization to reduce words to their root form, and part-of-speech tagging to identify the grammatical role of each word. They will also learn how to generate word embeddings using the BERT model. This knowledge will help Machine Learning Engineers improve the accuracy of their machine learning models.
See salaries and explore the career path for Machine Learning Engineer
Data Analyst
Data Analysts use data to solve business problems. This course teaches Data Analysts how to use text data to gain insights into customer behavior, market trends, and other business data. They will learn how to use natural language processing techniques to identify key themes and patterns in text data, and how to use machine learning models to predict future outcomes. This course may also be useful for Data Analysts who want to gain an understanding of how to generate word embeddings using the BERT model.
See salaries and explore the career path for Data Analyst
Sales Manager
Sales Managers are responsible for leading sales teams and achieving sales goals. This course teaches Sales Managers how to use text data to understand customer needs and identify sales opportunities. They will learn how to use natural language processing techniques to extract insights from text data, and how to use machine learning models to predict future outcomes. This knowledge will help Sales Managers improve their sales performance.
See salaries and explore the career path for Sales Manager
Customer Success Manager
Customer Success Managers are responsible for ensuring that customers are successful with a company's products and services. This course teaches Customer Success Managers how to use text data to understand customer needs and identify opportunities to improve customer satisfaction. They will learn how to use natural language processing techniques to extract insights from text data, and how to use machine learning models to predict future outcomes. This knowledge will help Customer Success Managers improve their customer retention rates.
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Technical Writer
Technical Writers create documentation for software, hardware, and other technical products. This course teaches Technical Writers how to use text data to create clear and concise documentation. They will learn how to use natural language processing techniques to identify key themes and patterns in text data, and how to use machine learning models to predict the readability of text. This knowledge will help Technical Writers produce better documentation that is easier for readers to understand.
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Content Writer
Content Writers create written content for websites, blogs, and other online platforms. This course teaches Content Writers how to use text data to create engaging and informative content. They will learn how to use natural language processing techniques to identify key themes and patterns in text data, and how to use machine learning models to predict the readability of text. This knowledge will help Content Writers produce better content that is more likely to be read and shared.
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Copywriter
Copywriters create written content for marketing and advertising campaigns. This course teaches Copywriters how to use text data to create persuasive and effective copy. They will learn how to use natural language processing techniques to identify key themes and patterns in text data, and how to use machine learning models to predict the readability of text. This knowledge will help Copywriters produce better copy that is more likely to convert readers into customers.
See salaries and explore the career path for Copywriter
UX Writer
UX Writers create written content for user interfaces. This course teaches UX Writers how to use text data to create clear and concise user interfaces. They will learn how to use natural language processing techniques to identify key themes and patterns in text data, and how to use machine learning models to predict the readability of text. This knowledge will help UX Writers produce better user interfaces that are easier for users to navigate.
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Information Architect
Information Architects design and organize websites and other online platforms. This course teaches Information Architects how to use text data to create clear and concise information architectures. They will learn how to use natural language processing techniques to identify key themes and patterns in text data, and how to use machine learning models to predict the readability of text. This knowledge will help Information Architects produce better information architectures that are easier for users to navigate.
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Librarian
Librarians organize and manage information resources. This course teaches Librarians how to use text data to improve the organization and accessibility of information resources. They will learn how to use natural language processing techniques to identify key themes and patterns in text data, and how to use machine learning models to predict the relevance of information resources. This knowledge will help Librarians create better libraries that are easier for users to find the information they need.
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Business Analyst
Business Analysts use data to help businesses make better decisions. This course teaches Business Analysts how to use text data to understand customer needs, identify market opportunities, and evaluate the effectiveness of marketing campaigns. They will learn how to use natural language processing techniques to extract insights from text data, and how to use machine learning models to predict future outcomes. This course may also be useful for Business Analysts who want to gain an understanding of how to generate word embeddings using the BERT model.
See salaries and explore the career path for Business Analyst
Product Manager
Product Managers are responsible for developing and launching new products. This course teaches Product Managers how to use text data to understand customer needs and identify market opportunities. They will learn how to use natural language processing techniques to extract insights from text data, and how to use machine learning models to predict future outcomes. This knowledge will help Product Managers make better decisions about which products to develop and how to market them.
See salaries and explore the career path for Product Manager
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. This course teaches Marketing Managers how to use text data to understand customer behavior and identify market trends. They will learn how to use natural language processing techniques to extract insights from text data, and how to use machine learning models to predict future outcomes. This knowledge will help Marketing Managers develop more effective marketing campaigns.
See salaries and explore the career path for Marketing Manager

Reading list

We've selected 12 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 Building Features from Text Data in Microsoft Azure.
Cover image
Natural Language Processing with Python
Save
Provides a comprehensive overview of natural language processing techniques. It covers a wide range of topics, including text preprocessing, tokenization, stemming, lemmatization, and machine learning for NLP. This book valuable resource for anyone who wants to learn more about NLP.
Natural Language Processing with Python: Analyzing...
Paperback
$$$
(中文) Python Natural Language Processing(Chinese Edition)
Paperback
$$
Natural Language Processing with Python: Analyzing...
Kindle Edition
$$
Cover image
Text Mining with R
Save
Provides a practical guide to text mining using the R programming language. It covers a wide range of topics, including text preprocessing, text mining techniques, and machine learning for text mining. This book valuable resource for anyone who wants to learn more about text mining.
Text Mining with R
Paperback
Check
Text Mining with R
Kindle Edition
Check
Cover image
Natural Language Processing in Action, Second...
Save
Provides a practical guide to NLP. It covers a wide range of topics, including text preprocessing, text mining techniques, and machine learning for NLP. This book valuable resource for anyone who wants to learn more about NLP.
Natural Language Processing in Action, Second...
Paperback
$$$
Cover image
Introduction to Natural Language Processing
Save
Provides a comprehensive overview of NLP. It covers a wide range of topics, including text preprocessing, text mining techniques, and machine learning for NLP. This book valuable resource for anyone who wants to learn more about NLP.
Introduction to Natural Language Processing...
Hardcover
$$$
Introduction to Natural Language Processing...
Kindle Edition
$$
Cover image
Practical Natural Language Processing
Save
Provides a practical guide to NLP. It covers a wide range of topics, including text preprocessing, text mining techniques, and machine learning for NLP. This book valuable resource for anyone who wants to learn more about NLP.
Practical Natural Language Processing: A...
Paperback
$$$
Practical Natural Language Processing: A...
Kindle Edition
$$
Cover image
Text Analytics with Python
Save
Provides a comprehensive overview of text analytics. It covers a wide range of topics, including text preprocessing, text mining techniques, and machine learning for text analytics. This book valuable resource for anyone who wants to learn more about text analytics.
Text Analytics with Python: A Practitioner's Guide...
Paperback
$$
Text Analytics with Python: A Practical Real-World...
Kindle Edition
$$
Cover image
Deep Learning with JavaScript
Save
Provides a comprehensive overview of machine learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and deep learning. This book valuable resource for anyone who wants to learn more about machine learning.
Deep Learning with JavaScript: Neural networks in...
Paperback
$$
Cover image
Deep Learning
Save
Provides a comprehensive overview of deep learning. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks. This book valuable resource for anyone who wants to learn more about deep learning.
Deep Learning
Paperback
$$$
Deep Learning (Adaptive Computation and Machine...
Hardcover
$$$
Deep Learning (Adaptive Computation and Machine...
Kindle Edition
$$$
Cover image
Machine Learning with PyTorch and Scikit-Learn
Save
Provides a comprehensive overview of machine learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and deep learning. This book valuable resource for anyone who wants to learn more about machine learning.
Machine Learning with PyTorch and Scikit-Learn:...
Kindle Edition
$$
Cover image
Deep Learning with Python, Second Edition
Save
Provides a comprehensive overview of deep learning. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks. This book valuable resource for anyone who wants to learn more about deep learning.
Deep Learning with Python, Second Edition
Paperback
$$
Deep Learning with Python, Second Edition
Kindle Edition
$$
Cover image
Machine Learning with R
Save
Provides a comprehensive overview of machine learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and deep learning. This book valuable resource for anyone who wants to learn more about machine learning.
Machine Learning with R - Fourth Edition: Learn...
Paperback
$$
Machine Learning with R - Second Edition: Expert...
Kindle Edition
$$
Machine Learning with R - Third Edition: Expert...
Paperback
$$
(Italiano) Machine Learning con R: Conoscere le tecniche per...
Kindle Edition
$$
R: Unleash Machine Learning Techniques
Kindle Edition
$$$
Machine Learning with R: Learn How to Use R to...
Paperback
$$
(中文) Machine learning and R language (3rd edition of the...
Paperback
$$
Cover image
Deep Learning with R, Second Edition
Save
Provides a comprehensive overview of deep learning. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks. This book valuable resource for anyone who wants to learn more about deep learning.
Deep Learning with R, Second Edition
Paperback
$$$
Deep Learning with R, Second Edition
Kindle Edition
$$

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Time
1 hours
Via
Pluralsight
Instructor
Michael Heydt
Building Features from Text Data in Microsoft Azure belongs to the following collections:
  1. Engineering Features for Machine Learning in Microsoft Azure
  2. Microsoft Azure Data Scientist (DP-100)
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Provides hands-on experience with Microsoft Azure Machine Learning Service virtual machines, ensuring familiarity with industry-standard tools
Taught by Michael Heydt, recognized for expertise in text data analysis and machine learning
Focuses on creating text features for machine learning models, aligning with the industry need for accurate data representation
Covers techniques such as text tokenization, frequency filtering, and n-gram identification, providing a comprehensive understanding of natural language processing
May require prior knowledge in machine learning, as it assumes familiarity with concepts like models and feature vectors
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