Please go through the introductory article in the series…
Topological Data Analysis is Superior to Pixel Based Methods i.e. Deep Learning
Lets consider TWO Scenarios
And the article below which describes the Theory of Topological Data Analysis and shows examples from another Python Tool for TDA called scikit-tda
In this article we are going to continue where we left off… and we will see topological data analysis with a python tool called Gudhi. Which is very mature and well tested.
Gudhi is NOT that well known amongst Data Scientists
The Gudhi library is an open source library for Computational Topology and Topological Data Analysis (TDA). It offers state-of-the-art algorithms to construct various types of simplicial complexes, data structures to represent them, and algorithms to compute geometric approximations of shapes and persistent homology.
The GUDHI library offers the following interoperable modules:
First, Lets Install Gudhi
conda install -c conda-forge gudhi
conda install jupyter notebook numpy pandas
pip install scipy matplotlib
Lets see how to create persistence diagrams and simplicial complexes…
Source Code [Jupyter Notebooks + Data Sets] & Github Repo
This is our website http://automatski.com