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Deep Learning on Mobile Devices – William Grisaitis

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Deep Learning on Mobile Devices – William Grisaitis

PyData Miami Meetup – March 5, 2019

PyData Miami / Machine Learning Meetup

Miami, FL
943 Machine Learners

Meetup group for researchers, students, and hobbyists in machine learning, neural networks, and statistics.Meetups can range between beginner tutorials (e.g. getting started …

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While GPUs have been instrumental in the deep learning revolution since 2012, smartphones can also run deep neural networks on their own hardware and exceed state-of-the-art image classification performance from just a few years ago. This is mostly due to advances in neural network design and model structures. Innovations like the depth-wise separable convolution, for example, have enabled more efficient computation in neural nets. Hardware has also advanced in terms of compute and memory capacity. Put together, a smartphone today can quickly classify images with a lightweight neural network with a higher accuracy than AlexNet achieved in 2012.


William Grisaitis is a machine learning engineer and curious person based in Orlando, Florida. William has worked in deep learning since 2016 when he joined a deep learning research lab at the HHMI Janelia Research Campus and contributed to peer-reviewed research in deep learning and computational neuroscience. He currently works as a freelance data science consultant and is currently exploring entrepreneurial opportunities involving deep learning on smartphones. Prior to 2016 William worked at Capital One in credit cards and small business lending. Born and raised in Orlando, William graduated with an A.B. in Physics from Duke University in 2012.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.




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00:02 so William per seconds is a machine

00:05 learning engineer and curious person in

00:07 Orlando you grow up girl I know I

00:08 graduated to Duke he did some work at

00:11 the Howard Hughes Medical Institute

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