Data analysis, statistics, and mathematics have been revolutionized by increases in computing power -- and now it's happening again. We can go beyond traditional statistical approaches to data by using unsupervised learning techniques and advanced math.

Topological data analysis looks at the shape of data -- the underlying structure -- and in revealing surprising insights, it also brings up interesting questions. The best part is that you can do your own analysis with Python and R, free and open-source tools. We'll look at real-life applications of topological data analysis from "the dieting paradox" in human health to the health of financial networks, and I'll ask you how topology might apply to your big data problems!

============================

Thanks for reading :heart: If you liked this post, share it with all of your programming buddies! Follow me on Facebook | Twitter

Learn More

☞ Machine Learning A-Z™: Hands-On Python & R In Data Science

☞ Python for Data Science and Machine Learning Bootcamp

☞ Machine Learning, Data Science and Deep Learning with Python

☞ [2019] Machine Learning Classification Bootcamp in Python

☞ Introduction to Machine Learning & Deep Learning in Python

☞ Machine Learning Career Guide – Technical Interview

☞ Machine Learning Guide: Learn Machine Learning Algorithms

☞ Machine Learning Basics: Building Regression Model in Python

☞ Machine Learning using Python - A Beginner’s Guide

#machine-learning

The Shape of Data: Machine Learning and Topology
13.15 GEEK