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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
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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
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Getting Started with Natural Language Processing with Python with these
activities:
Review Course Materials
Show steps
Strengthen your foundation and prepare for the course by reviewing the core concepts, algorithms, and tools covered in the course materials.
Browse courses on
Machine Learning Algorithms
Show steps
-
Review the course syllabus and identify key topics.
-
Go through lecture notes and slides.
Review 'Natural Language Processing with Python'
Show steps
Familiarize yourself with the foundational concepts and techniques of NLP by reading this comprehensive book.
View
Natural Language Processing with Python:...
on Amazon
Show steps
-
Read the chapters covering topics relevant to the course.
-
Complete the exercises to reinforce your understanding.
Practice Text Pre-processing with Natural Language Toolkit
Show steps
Build a strong foundation in text pre-processing using Natural Language Toolkit, which you'll use throughout the course.
Browse courses on
Natural Language Toolkit
Show steps
-
Install Natural Language Toolkit and familiarize yourself with its functions.
-
Practice tokenizing, stemming, and removing stop words from sample text.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Explore Text Scraping with BeautifulSoup
Show steps
Enhance your abilities to extract text data from websites, which is crucial for many NLP applications.
Browse courses on
BeautifulSoup
Show steps
-
Learn how to use BeautifulSoup to find and extract specific text elements.
-
Practice scraping text from sample websites.
Attend an NLP Workshop for Hands-on Experience
Show steps
Gain practical experience and learn from experts by attending an NLP workshop, enhancing your understanding of real-world applications.
Show steps
-
Research and identify relevant NLP workshops.
-
Register and attend the workshop.
-
Participate actively in discussions and exercises.
Develop an Automated Text Summarization Tool
Show steps
Apply your understanding of machine learning to build a tool that automatically summarizes text, a valuable skill for various industries.
Browse courses on
Text Summarization
Show steps
-
Choose a machine learning algorithm and train it on a dataset of text summaries.
-
Implement the trained model into a tool that can summarize new text.
Participate in a Text Classification Competition
Show steps
Challenge yourself and refine your skills by participating in a text classification competition, where you'll apply your knowledge to real-world problems.
Browse courses on
Text Classification
Show steps
-
Find a relevant text classification competition to participate in.
-
Train and optimize your text classification model.
-
Submit your model and track your results.
Build a Text Analysis Dashboard
Show steps
Demonstrate your proficiency by creating an interactive dashboard that visualizes and analyzes text data, providing valuable insights.
Browse courses on
Data Visualization
Show steps
-
Design the dashboard and identify the key metrics to track.
-
Develop the backend code to extract and process text data.
-
Create interactive visualizations using a data visualization library.
-
Deploy the dashboard and share it for feedback.
Review Course Materials
Show steps
Strengthen your foundation and prepare for the course by reviewing the core concepts, algorithms, and tools covered in the course materials.
Browse courses on
Machine Learning Algorithms
Show steps
Show steps
Show steps
- Review the course syllabus and identify key topics.
- Go through lecture notes and slides.
Review 'Natural Language Processing with Python'
Show steps
Familiarize yourself with the foundational concepts and techniques of NLP by reading this comprehensive book.
View
Natural Language Processing with Python:...
on Amazon
Show steps
Show steps
Show steps
- Read the chapters covering topics relevant to the course.
- Complete the exercises to reinforce your understanding.
Practice Text Pre-processing with Natural Language Toolkit
Show steps
Build a strong foundation in text pre-processing using Natural Language Toolkit, which you'll use throughout the course.
Browse courses on
Natural Language Toolkit
Show steps
Show steps
Show steps
- Install Natural Language Toolkit and familiarize yourself with its functions.
- Practice tokenizing, stemming, and removing stop words from sample text.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Explore Text Scraping with BeautifulSoup
Show steps
Enhance your abilities to extract text data from websites, which is crucial for many NLP applications.
Browse courses on
BeautifulSoup
Show steps
Show steps
Show steps
- Learn how to use BeautifulSoup to find and extract specific text elements.
- Practice scraping text from sample websites.
Attend an NLP Workshop for Hands-on Experience
Show steps
Gain practical experience and learn from experts by attending an NLP workshop, enhancing your understanding of real-world applications.
Show steps
Show steps
Show steps
- Research and identify relevant NLP workshops.
- Register and attend the workshop.
- Participate actively in discussions and exercises.
Develop an Automated Text Summarization Tool
Show steps
Apply your understanding of machine learning to build a tool that automatically summarizes text, a valuable skill for various industries.
Browse courses on
Text Summarization
Show steps
Show steps
Show steps
- Choose a machine learning algorithm and train it on a dataset of text summaries.
- Implement the trained model into a tool that can summarize new text.
Participate in a Text Classification Competition
Show steps
Challenge yourself and refine your skills by participating in a text classification competition, where you'll apply your knowledge to real-world problems.
Browse courses on
Text Classification
Show steps
Show steps
Show steps
- Find a relevant text classification competition to participate in.
- Train and optimize your text classification model.
- Submit your model and track your results.
Build a Text Analysis Dashboard
Show steps
Demonstrate your proficiency by creating an interactive dashboard that visualizes and analyzes text data, providing valuable insights.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Design the dashboard and identify the key metrics to track.
- Develop the backend code to extract and process text data.
- Create interactive visualizations using a data visualization library.
- Deploy the dashboard and share it for feedback.
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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