The Fifth Elephant 2018

The seventh edition of India's best data conference

Topological Data Analysis Theory and Practice

Submitted by Milan Joshi (@mlnjsh) on Aug 17, 2017

Section: Full talk Technical level: Intermediate Status: Rejected

Abstract

As we are already living in the age of big data and it is too big to ignore. Therefore it is important that we find ways to explore, summarize , and answer questions with this data. However the problem is not just that the data is big, but that it is complicated, loaded with surprising patterns, unusual structures, Often that means it is even too complicated for the standard methods to be useful . In this Talk I will discuss a new collection of tools available from the field known collectively as Topological data analysis(TDA). TDA is relatively new branch of Mathematics , it’s an approach to extract shapes(patterns) in data and obtain insights from datasets using techniques from topology, Topology is very old branch of pure Mathematics. I will discuss about the technology called Persistent homology , Barcodes, Persistent Landscape in TDA .Finally we also discuss the scope and future of this field with few applications and some tools and software’s in which TDA can be done .

Outline

What is Topology
what is topological data analysis
What is Persistent Homology
What is Mapper Algorithm
How it helps in solve complex problems
How it differs from traditional machine Learning
How to do TDA in R
Some Applications

Requirements

laptops and R software installed

Speaker bio

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