Tue, Jan 31, 2017 • Events

SmartData Conference 2017

Scott Purdy • Director of Engineering

How to Model Streaming Data That You Know Nothing About

Data modeling usually involves an array of algorithms, each with different
assumptions about the data, hand tuned sets of inputs and parameters, and a
tremendous amount of domain expertise. But can we model data if we don’t know
anything about it? What assumptions about the data can we make? And can we use
these assumptions as building blocks for more general algorithms? In this talk,
we will explore the fundamentals of unsupervised learning with streaming data.
We will show how these fundamentals are used in modern machine learning
techniques and how they can be implemented generally and applied across types of
streaming data. And we will show some applications and libraries leveraging them
that you can use today.

You will learn:

  • What it means to model streaming data that you know nothing about

  • How to find structure and extract information from novel streams of data

  • How modern algorithms are using these techniques to solve challenging problems

  • What types of applications benefit most from unstructured learning

  • Concrete demonstrations of the application to streaming prediction, anomaly
    detection, and classification tasks
Scott Purdy • Director of Engineering

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