Learn the essential techniques for cleansing and processing text in Python. Discover how to convert text to a form that's ready for analytics and predictions.
- [Kumaran P] Let's say you have a massive amount of text that you need to analyze. That's a fairly likely scenario considering more and more text is being generated today. It takes the form of messages, emails, blogs, and comments on social media. Hand in hand, the need to understand, analyze, and act on these data is also growing. As such, text processing and analytics is a key skill for any data professional. My name is Kumaran Ponnambalam. In this course, I will show you the tools and techniques available for text processing in Python. We will use NLTK library to build use cases in Jupyter notebooks. You need prior familiarity with Python 3.7 and Jupyter notebooks. That being said, let's explore on how to do processing and transformation of text with Python.
- Text mining today
- Reading text files using Python
- Cleansing text data
- Build n-grams databases for text predictions
- Preparing TF-IDF matrices for machine learning
- Scaling text processing for performance