Applications of Statistical Learning with Python

Course details

Scientists have been increasingly using Python for data analysis tasks such as natural language processing and computer vision, and a new wave of modules and packages, make programming these tasks easier than ever. In this course, youll dive into Natural Language Processing and get familiar with the NLTK package. This video course is filled with real-world, practical examples that show you Pythons true power as a programming language for data analysis.

Youll learn to read text in documents using different models, and employ sentiment analysis to predict the authors intent. Youll also see how to employ Python to read images and for computer vision. Once youve learned to employ specific Python packages and syntax for these tasks, youll explore case studies that put forth solid real-world examples on spam filtering and analyzing human emotions through a dictionary of images.

The code bundle for this video course is available.

About the Author

Curtis Miller is Associate Instructor at the University of Utah, and an MSTAT student. He is currently involved in research on data analysis from statistical and computer science perspectives. Curtis has published research on policy and economic issues.