
Hunting for the Higgs
Machine learning and particle physics go together…
November 16, 201410m 16s
Audio is streamed directly from the publisher (feeds.soundcloud.com) as published in their RSS feed. Play Podcasts does not host this file. Rights-holders can request removal through the copyright & takedown page.
Show Notes
Machine learning and particle physics go together like peanut butter and jelly--but this is a relatively new development.
For many decades, physicists looked through their fairly large datasets using the laws of physics to guide their exploration; that tradition continues today, but as ever-larger datasets get made, machine learning becomes a more tractable way to deal with the deluge.
With this in mind, ATLAS (one of the major experiments at CERN, the European Center for Nuclear Research and home laboratory of the recently discovered Higgs boson) ran a machine learning contest over the summer, to see what advances could be found from opening up the dataset to non-physicists.
The results were impressive--physicists are smart folks, but there’s clearly lots of advances yet to make as machine learning and physics learn from one another. And who knows--maybe more Nobel prizes to win as well!
https://www.kaggle.com/c/higgs-boson
Topics
datasciencemachinelearninglineardigressions