The Deep End of Data Science

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One of the most exciting new fields in Data Science is something called “deep learning.” Deep learning is an area of machine learning research focused on

“teaching machines to think more hierarchically or more contextually”

enabling significant advances in Natural Language Processing (NLP), image recognition, and other machine learning interests according to Derrick Harris of GigaOm.

While improving a machine’s ability to better recognize images may not seem as important as finding cures to deadly diseases researchers at Google are using deep learning to build everything from safe self-driving cars to providing an elegant voice search experience on your mobile device.

But, once deep learning tools and techniques expand beyond the domains of research labs in Silicon Valley industries from healthcare to finance are ripe for disruption from innovators armed with these new capabilities.

MIT Technology Review named deep learning a top ten breakthrough in 2013 and now the data science community is looking for ways to learn more about it.

If you would like to learn more about deep learning come check out Data Science ATL’s very own Dr. Andrew Gardner, PhD (@AndyWocky) present Deep Learning for Data Scientists the evening of Wednesday December 11th.

RSVP today as this event already has nearly 100 200+ members and guests planning to attend!

Travis Turney (@travturn)
Co-founder Data Science ATL

One thought on “The Deep End of Data Science

  1. Pingback: Raw: advanced data visualization via cut and paste | Knowledge Strategies & Bioscience

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