How to Get Started with Deep Learning in Computer Vision
Date: This event took place live on July 24 2014
Presented by: Pete Warden
Duration: Approximately 60 minutes.
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Hosted By: Ben Lorica
There have been big improvements in image analysis over the last few years thanks to the adoption of deep learning neural networks to solve vision problems, but figuring out how to get started with them isn't easy.
In this webcast Pete Warden will walk through some popular open-source tools from the academic world, and show you step-by-step how to process images with them. Starting right from downloading the source and data, setting up the dependencies and environment, compiling, and then executing the libraries as part of a program, you'll be shown how to solve your own computer vision problems.
About Pete Warden
Pete is the CTO of Jetpac Inc, a startup focused on analyzing billions of public photos. He's been a recipient of an NSF grant for his computer vision work, worked on image processing at Apple for five years, and has published a number of popular open source data analysis projects and O'Reilly books. He blogs at https://petewarden.com and is @petewarden on Twitter.
About Ben Lorica
Ben Lorica is the Chief Data Scientist and Director of Content Strategy for Data at O'Reilly Media, Inc.. He has applied Business Intelligence, Data Mining, Machine Learning and Statistical Analysis in a variety of settings including Direct Marketing, Consumer and Market Research, Targeted Advertising, Text Mining, and Financial Engineering. His background includes stints with an investment management company, internet startups, and financial services. He writes regularly about Big Data and Data Science on the O'Reilly Data blog.
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