Getting Started with Natural Language Processing with Python
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.
What you'll learn
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.
Table of contents
- Recognizing Natural Language Processing Applications 7m
- Understanding NLP Tasks 4m
- Tokenizing Text 3m
- Removing Stopwords 3m
- Identifying Bigrams 2m
- Stemming and POS Tagging 3m
- Disambiguating Word Meanings 3m
- Contrasting Rule Based and Machine Learning Approaches 4m
- Understanding Types of Machine Learning Problems in NLP 5m
- Understanding the Mechanics of Machine Learning 4m