July 20–24, 2015
Portland, OR

Data transformation superpowers with digital signal processing

A boyle (New Relic)
1:40pm–2:20pm Thursday, 07/23/2015
Solve E147/148
Tags: Python
Average rating: ****.
(4.25, 4 ratings)
Slides:   external link

Prerequisite Knowledge

Basic algebra


Want to understand the “magic” behind speech recognition, image manipulation, and data compression? The world is full of signals, and digital signal processing (DSP) allows us to interpret and manipulate them, leveraging the power of computers. Images, audio, video, temperature, pressure, tweets, anything measurable in time and/or space can be represented as a digital signal, and analyzed using DSP. Learn what DSP is, and how you can use it to look at data, and the world around you, with a new critical eye.

DSP has a reputation of being hard to learn, but you do not need profound analytical skills or an extensive background in mathematics to grasp the fundamental concepts. If you know basic algebra, and you know what a sine wave is, you can learn the basics of DSP.

There are some great open source libraries for employing DSP. I will provide examples using Python and the SciPy package.

Photo of A boyle

A boyle

New Relic

Amy Boyle is a senior software engineer at New Relic focusing on the core data platform. She works in distributed systems, stream processing, and lots of data.