In this talk, Adam Laiacano from Tumblr gives an "Introduction to Digital Signal Processing in Hadoop". Adam introduces the concepts of digital signals, filters, and their interpretation in both the time and frequency domain, and he works through a few simple examples of low-pass filter design and application. It's much more application focused than theoretical, and there is no assumed prior knowledge of signal processing. This talk was recorded at the NYC Machine Learning Meetup at Pivotal Labs.
Adam also works through how they can be used either in a real-time stream or in batch-mode in Hadoop (with Scalding). I'll hopefully have some examples of how to detect trendy meme-ish blogs on Tumblr.
Bio: Adam Laiacano is a Data Scientist and Engineer at Tumblr, a blogging network with over 140 million blogs, where he's responsible for collecting and analyzing large volumes of data to gain a better understanding of trends and activity within the Tumblr community. He holds a Bachelor of Science degree in Electrical Engineering from Northeastern University, and designed signal detection systems for low-power atomic clocks before joining Tumblr.