How does Topological Data Analysis improve ML applications?

A whitepaper from Ayasdi outlines the way in which Topological Data Analysis (TDA) enhances ML applications

How does Topological Data Analysis improve ML enterprise applications?

Topological Data Analysis (TDA) operates as the underlying technology in Ayasdi’s award-winning artificial intelligence platform. According to the company’s recent whitepaper, TDA also distills “business value from large, complex datasets.”

The challenge

At present, the “quantity of possible insights in a given dataset is an exponential function of the number of data points”, Ayasdi notes. The company also highlights that “aggregate data growth is an exponential function with time.”

As a result, it is impossible to train enough data scientists to tackle this “double-exponential demand curve” with ease. Nevertheless, TDA has the ability to improve both the quality and speed of analytics engines.

In effect, TDA is an approach to data analysis using techniques from the mathematical discipline topology. As Ayasdi observes, TDA also “draws on the philosophy that all data has an underlying shape and that shape has meaning.”

The power of TDA

The Ayasdi Machine Intelligence Platform utilises the power of TDA in order to provide cutting-edge data analysis. In fact, the platform draws together a broad range of machine learning, statistical, and geometric algorithms.

In turn, this creates a “summary or compressed representation of all the data points in a large data set” in order to reveal patterns and relationships. TDA is thus an extremely efficient way of “partitioning data to understand the underlying properties that characterise the segments and sub-segments” that lie within data.

The combination of TDA and machine learning provides a unique and powerful infrastructure. In fact, it enhances a company’s ability to “draw meaning from data that is highly resistant to other methods of analysis and interpretation.”

Moreover, Ayasdi’s platform supports a whole suite of application technologies. These applications facilitate the “design, development, and deployment of intelligent applications” and serve specific vertical markets.

Notably, this advanced analytics software constructs “highly interactive visual networks” for companies. This therefore allows enterprises to rapidly explore and understand critical patterns and relationships within a data set.

It is evident that the combination of TDA and machine learning provides invaluable data insights. Nevertheless, Ayasdi’s Machine Intelligence Platform is the only commercially available implementation of TDA at present.

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