This is the code repository for Applications of Statistical Learning with Python [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
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, you’ll 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 Python’s true power as a programming language for data analysis.
You’ll learn to read text in documents using different models, and employ sentiment analysis to predict the author’s intent. You’ll also see how to employ Python to read images and for computer vision. Once you’ve learned to employ specific Python packages and syntax for these tasks, you’ll explore case studies that put forth solid real-world examples on spam filtering and analyzing human emotions through a dictionary of images.
- Look for specific signs and intents using natural language processing
- Find specific points and figures within images using computer vision
- Detect spam by analyzing data within emails
- Detect emotion by reading patterns within images
- Employ different filters and transforms to analyze and manipulate data
To fully benefit from the coverage included in this course, you will need:
This course has the following software requirements: