Getting Started with Natural Language Processing with Python
Pluralsight
Course Summary
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.
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Course Description
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.
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Course Syllabus
Course Overview- 1m 47s
—Course Overview 1m 47sGetting Started- 35m 55s
—Recognizing Natural Language Processing Applications 6m 51s
—Understanding NLP Tasks 4m 0s
—Tokenizing Text 2m 33s
—Removing Stopwords 2m 43s
—Identifying Bigrams 2m 12s
—Stemming and POS Tagging 2m 48s
—Disambiguating Word Meanings 2m 37s
—Contrasting Rule Based and Machine Learning Approaches 3m 46s
—Understanding Types of Machine Learning Problems in NLP 4m 44s
—Understanding the Mechanics of Machine Learning 3m 35sAuto-summarizing Text- 26m 35sClassifying Text Using Machine Learning- 39m 26s
