Learn about the techniques for analyzing text data in Python and perform machine learning and predictions.
- [Kumaran] 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. And in hand, the need to understand, analyze and act on this 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 techniques and tools available for text analytics and predictions in Python. We will use nltk and scikit-learn libraries to build use cases in Jupyter Notebooks. You need prior familiarity with Python 3.7, Jupyter Notebooks and machine learning. That being said, let's explore on how to do text analytics and machine learning in Python.
- Generating a word cloud
- Determining the sentiments of customers
- K-means clustering of text
- Predicting the classification of text documents
- Predictive text