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Applications of Statistical Learning with Python [Video]

More Information
Learn
  • 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
About

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.

The code bundle for this video course is available at : https://github.com/PacktPublishing/Applications-of-Statistical-Learning-with-Python

Style and Approach

This course contains in-depth content balanced with tutorials that put theory into practice. This course will give you both a theoretical understanding and practical exp with examples that will allow you indulge in the art of statistical modeling and analysis using the Python programming language.

Features
  • Solid examples to help you wrap your head around the application of statistical modeling using Python
  • Filled with real-world, practical examples that show you how to jump in and start building effective prediction models
  • Covers the important concepts such sentiment analysis and test processing with the help of Python
Course Length 1 hour 44 minutes
ISBN9781788295499
Date Of Publication 28 May 2018
Looking at the Pictures
Learning to Feel – Training the Model

Authors

Curtis Miller

Curtis Miller is a graduate student at the University of Utah, seeking an Master’s in Statistics (MSTAT) and a Big Data Certificate.

In the past, Curtis has worked as a Math Tutor, and has a double major adding mathematics with an emphasis in statistics as a second major.

Curtis has studied the gender pay gap, and presented his paper or Gender Pay Disparity in Utah, which grabbed the attention of local media outlets.

He currently teaches Basic Statistics at the University of Utah. He enjoys writing and is an avid reader, and enjoys studying politics, economics, history, and psychology and sociology.