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Getting Started with Natural Language Processing with Python
Swetha Kolalapudi
Swetha Kolalapudi
This course is all about taking raw text data and deriving insights and value from it--processing text data using standard techniques in Natural Language Processing and Machine Learning.
Read more
This course is all about taking raw text data and deriving insights and value from it--processing text data using standard techniques in Natural Language Processing and Machine Learning.
Read more
This course is all about taking raw text data and deriving insights and value from it--processing text data using standard techniques in Natural Language Processing and Machine Learning.
Text data is available in abundance on the Internet, whether it be reviews, tweets, surveys, web pages or emails. Natural language processing is a powerful skill that helps you derive immense value from that data. In this course, Getting Started with Natural Language Processing with Python, you'll first learn about using the Natural Language Toolkit to pre-process raw text. Next, you'll learn how to scrape websites for texting using BeautifulSoup, as well as how to auto-summarize text using machine learning. You'll wrap up the course by exploring how to classify text using machine learning. By the end of this course you'll be able to confidently process raw text data and apply machine learning algorithms to it.
Register for this course and see more details by visiting:
OpenCourser.com/course/ao3las/getting
What's inside
Syllabus
Course Overview
Getting Started
Auto-summarizing Text
Classifying Text Using Machine Learning
Read more
Syllabus
Course Overview
Getting Started
Auto-summarizing Text
Classifying Text Using Machine Learning
Read more
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores text data processing using industry standard NLP and ML techniques
Taught by Swetha Kolalapudi, an experienced instructor in the field
Suitable for beginners and those looking to strengthen their NLP and ML skills
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Activities
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Getting Started with Natural Language Processing with Python.
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Career center
Learners who complete Getting Started with Natural Language Processing with Python will develop knowledge and skills
that may be useful to these careers:
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers are responsible for developing and deploying NLP models. This course can help you develop the skills you need to be a successful NLP Engineer, including how to use Python to process text data and how to use machine learning to analyze text data.
Data Scientist
Data Scientist
Data Scientists are responsible for extracting insights from data, which can be used to make better decisions. This course can help you develop the skills you need to be a successful Data Scientist, including how to use Python to process text data and how to use machine learning to analyze text data.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for building and deploying machine learning models. This course can help you develop the skills you need to be a successful Machine Learning Engineer, including how to use Python to process text data and how to use machine learning to analyze text data.
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data. This course can help you develop the skills you need to be a successful Data Analyst, including how to use Python to process text data and how to use machine learning to analyze text data.
Software Engineer
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. This course can help you develop the skills you need to be a successful Software Engineer, including how to use Python to process text data and how to use machine learning to analyze text data.
Web Developer
Web Developer
Web Developers are responsible for designing and developing websites. This course can help you develop the skills you need to be a successful Web Developer, including how to use Python to process text data and how to use machine learning to analyze text data.
Information Architect
Information Architect
Information Architects are responsible for designing and organizing information systems. This course can help you develop the skills you need to be a successful Information Architect, including how to use Python to process text data and how to use machine learning to analyze text data.
Content Strategist
Content Strategist
Content Strategists are responsible for planning and creating content for websites and other marketing materials. This course can help you develop the skills you need to be a successful Content Strategist, including how to use Python to process text data and how to use machine learning to analyze text data.
UX Designer
UX Designer
UX Designers are responsible for designing the user experience of websites and applications. This course can help you develop the skills you need to be a successful UX Designer, including how to use Python to process text data and how to use machine learning to analyze text data.
Marketing Manager
Marketing Manager
Marketing Managers are responsible for planning and executing marketing campaigns. This course can help you develop the skills you need to be a successful Marketing Manager, including how to use Python to process text data and how to use machine learning to analyze text data.
Technical Writer
Technical Writer
Technical Writers are responsible for writing technical documentation, such as user manuals and white papers. This course can help you develop the skills you need to be a successful Technical Writer, including how to use Python to process text data and how to use machine learning to analyze text data.
Customer Success Manager
Customer Success Manager
Customer Success Managers are responsible for ensuring that customers are satisfied with a company's products and services. This course can help you develop the skills you need to be a successful Customer Success Manager, including how to use Python to process text data and how to use machine learning to analyze text data.
Sales Manager
Sales Manager
Sales Managers are responsible for leading and managing sales teams. This course can help you develop the skills you need to be a successful Sales Manager, including how to use Python to process text data and how to use machine learning to analyze text data.
Product Manager
Product Manager
Product Managers are responsible for planning and developing new products. This course can help you develop the skills you need to be a successful Product Manager, including how to use Python to process text data and how to use machine learning to analyze text data.
Business Analyst
Business Analyst
Business Analysts are responsible for analyzing business processes and making recommendations for improvement. This course can help you develop the skills you need to be a successful Business Analyst, including how to use Python to process text data and how to use machine learning to analyze text data.
For more career information including salaries, visit:
OpenCourser.com/course/ao3las/getting
Reading list
We've selected ten 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
Getting Started with Natural Language Processing with Python.
Provides a comprehensive guide to deep learning with Python. Covers fundamental concepts, architectures, and applications, and includes code examples and exercises.
Provides a comprehensive overview of deep learning techniques for natural language processing. Covers advanced topics such as transformer models and attention mechanisms.
Comprehensive reference covering the theory and practice of speech and language processing, including natural language processing. Useful for researchers, students, and practitioners.
Comprehensive textbook covering fundamental concepts of NLP with Python. Provides hands-on examples and exercises, and serves well as an introductory text or reference guide for students and practitioners.
Provides a rigorous introduction to the statistical foundations of natural language processing, including probabilistic models and machine learning techniques. Useful for students and researchers interested in the theoretical underpinnings of NLP.
Provides a practical introduction to machine learning with R. Covers supervised and unsupervised learning techniques, and includes code examples and exercises.
Introduces the Natural Language Toolkit (NLTK), a widely used Python library for natural language processing. Provides practical examples and exercises for various NLP tasks.
Provides a practical guide to natural language processing with Python, focusing on real-world applications. Includes code examples and exercises, and is suitable for both beginners and experienced practitioners.
Provides a guide to using SAS for natural language processing tasks. Covers text mining, machine learning, and deep learning techniques.
Provides an overview of social media mining techniques, including text analysis and sentiment analysis. Covers both theoretical and practical aspects of social media data analysis.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ao3las/getting
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Time
103 hours
Level
Introductory
Via
Pluralsight
Instructor
Swetha Kolalapudi
Language
English
Good to know
Explores text data processing using industry standard NLP and ML techniques
Taught by Swetha Kolalapudi, an experienced instructor in the field
Suitable for beginners and those looking to strengthen their NLP and ML skills
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